This week’s post discusses where we are at in the business cycle. Inflation expected to peak in H2/2022. As inflation is a lagging indicator, past price changes may be used to help forecast inflation (we have included our model in the attachment below). Changes in monetary policy has tended to take some time (between 12-24 months) to reflect its impact in inflation.
World Trade Volume appears to be slowing = Deflationary impulse (Expect lower USD Liquidity/higher US dollar(DXY) ahead). We started to see economic sensitive commodity price momentum slowing (i.e. copper) as it appears to have peaked in May and rolling over as liquidity (Central Bank and Private Liquidity) continues to decline. China’s central bank liquidity growth has been tightening as well, which tends to be correlated well with growth in commodity prices.
Historically, Labour (wages) and commodity prices tend to be the last measures to peak and rollover before a recession. The June Jobs report was released late last week. Nonfarm payrolls increased 372,000 in the month, better than the 250,000 Dow Jones estimate. Employment continued to grow in June. However, we are always looking for changes in trend/momentum, and there are some signs that the labour market may be rolling over soon as the marginal cost of labour (Job Openings/Unemployment Level) appears to be peaking for the cycle. Job Openings may have peaked in April 2022 and have declined in May and June. We see wage growth has potentially peaked while unemployment rate is at a trough. Initial Jobless Claims have also been rising since April 2022 month-over-month and average hours per week and overtime hours per week, declined slightly from May.
Despite lower growth impulse, Central Banks are expected to maintain hawkish stance until inflation pressure subsides and rate hikes are expected to chase inflation prints (which are lagging indicators). We do not expect a Central Bank pivot despite lower growth trajectory, until inflation is sustainability under control. In such an environment, the US dollar is expected to strengthen.
Beowulf ‘s Treasury Tactical Asset Allocation portfolios have been in the Safety portfolio based on BT Global Risk indicator since January 2022, as result of slowing momentum in Global Liquidity (Current Holdings: UUP, TFLO, SHV). See Beowulf’s Armory for Updates to the Model Portfolios for July 2022 positions.
Financial conditions have tightened significantly resulting in higher costs (higher interest rates/credit spreads/stronger USD) which is meant to reduce aggregate demand and consumption to bring aggregate demand back in line with the aggregate supply of goods and services in the global economy.
This process will reduce inflation back to Central Bank inflation targets. Changes in the Financial Conditions affect the Business Cycle/Liquidity cycle (borrowing/lending). Tightening cycles have tended to last 24 months. It is expected that growth in the economy will slow as well.
However, it takes a while to see the impact across the entire economy, company earnings, and inflation (which is a lagging indicator) and impact the expectations across all asset markets and borrowing and lending decisions.
We have looked at the last 11 periods in which the ISM PMI survey (proxy of GDP growth and aggregate demand) and impact of financial conditions (from 9 months prior) to determine the impact on equity markets and if we have reached a bottom. As of the closing price on Friday, we are down ~23% on the S&P 500 from the peak.
We note that the ISM PMI has slowed significantly in the past 4 months and try to model out based on past episodes where the path may take us. We examine other leading indicators as well. See below for our research on the topic.
Over the past 5 months, we have been laying our views on the Economy and Financial Markets. In the process, we have been taking our readers on this journey as we have been building up our investment framework and related methodology.
We plan to review and monitor the Trend Following strategies we have covered in our previous two posts as summarized going forward on this website every month in the Beowulf’s Amory section of the website.
There are 14 tracking portfolios that are based on trend following strategies that we have previously covered in our posts. Trend following has a long history of academic and empirical support. Evidence suggests that trend following can be an effective means of avoiding large negative returns that coincide with traditional bear markets/drawdowns and we have demonstrated this in our prior post.
In the current environment, our Wave Runner strategy combined with any risk asset strategy would have protected investor capital in the latest drawdown/equity bear market we are currently seeing in risk assets thus far in 2022.
The underlying economic justification for trend following rules lies in behavioral finance tenets such as those relating to herding, disposition, confirmation effects, and representativeness biases. At times information travels slowly, especially if assets are illiquid and/or if there is high information uncertainty; this leads to investor under-reaction. If investors are reluctant to realize small losses then momentum is enhanced via the disposition effect.
Our global risk indicator which captures both fundamental leading indicators (Global Liquidity and OECD Composite Leading Indicator) and market sentiment, has been in Risk-off mode since January 2022 and invested in our Safety Portfolio. Table 1 below shows YTD 2022 results across all 14 portfolios relative to Benchmarks (AWCI MSCI All-World Index and the S&P 500).
In 2022, global equity markets have been impacted by interest rate normalization by global central banks and higher than expected inflation, which has reduced asset values which some indexes such as NASDAQ 100 (QQQ) down by >20% from the previous peak. This brings to mind a quote attributed to Warren Buffett when considering the current market, “When the [economic/liquidity] tide goes out you get to see who’s swimming naked.”
The reduction of liquidity/increase in interest rates has particularly hurt businesses that have benefitted from the ongoing liquidity support and cheap money in the recent past, which are financing growth with little to no profit/significant cash flow in the short term, and the potential for turning a profit is very far out into the future. When the price of money changes (interest rates), all asset prices are re-rated.
This ‘reserve wealth effect’ will potentially result in lower aggregate demand/consumption, and Central Bank hope to bring aggregate demand back in line with supply which has been constrained due to COVID-19 and the Russia/Ukraine war. The rebalance of demand/supply is thought to cool the highest inflation we have seen in a generation. Our trend following strategy has outperformed the benchmarks as 12 out of 14 trend following portfolios remain in positive territory for year-to-date 2022.
Our BT Momentum portfolio which reviews all 107 ETFs on a relative momentum basis across all asset classes (Commodities, Country, Sector, Factor Anomalies, Market-Cap, Fixed Income/Currency) and invests in the top 3 based on prior month’s relative momentum, has seen the highest returns at 21% year-to-date given strength of energy-related commodities (oil, natural gas, and gasoline) and restricted supply, which has protected capital on a real-returns basis given the current high inflation regime.
Table 1 – Year-to-Date 2022 Performance
What we are Watching Going Forward.
As we have explained in prior posts, the rate of change of parameters within the economy is a lot more important to markets, rather than the absolute magnitude or level. Whether or not the terminal Fed Funds Rate is 2.50% or 3.50% is less important than the overall rate of change in the cost of financing for businesses and households relative to their incomes.
Coming out of the COVID-19 pandemic, aggregate debt levels are larger than pre-pandemic, so it’s important to understand the relative changes in both interest rates, and corporate credit spreads.
These inputs are very important in the cost structure of many companies as they look to refinance maturing debt in a highly financialized economy and may have a significant impact on corporate profit margins, given the rate of change, as well as wage growth. Historically, corporate profit margins or reduction in demand, have been defended by temporary layoffs of workers.
In Table 2, we note historically (going back to 1965) as interest rates have increased (represented by 10-year yield), investment credit spreads and unemployment have increased with a 6-9 month lag as corporates look to protect profit margins as demand/consumption may reduce overtime in 2022 due to the ‘reverse wealth effect’ in both stock and housing markets. We note that in April 2022, interest rates have hit a 3x z-score, which has historically signaled a peak and is followed by a widening of credit spreads/higher unemployment in the next 6-9 months.
To date in 2022, labor markets appear strong with job vacancies outpacing unemployed and wage growth robust at ~6%, though running below inflation. The structural deflationary trends that existed before the pandemic still exist, namely, high debt levels, demographics, and innovative technology – are still there. Does high inflation change this calculus? It remains to be seen what the answer to this question is and our investment framework will answer this question over time, as our investment framework takes into account the rate of change and invests based on relative momentum based on the rate of change, we expect to see how higher interest rates may play out over time across asset classes. We do not need to answer this question correctly or have a correct forecast of these dynamics to see our investment portfolio benefit.
Table 2 – US Investment Grade Credit Spreads, Interest Rates, and Unemployment
We hope that you have found this informative and endeavor to provide updates to the 14 portfolios going forward every month.
If you are interested in implementing these portfolio strategies or had any questions, feel free to contact us at email@example.com.
Berkshire Hathaway’s returns since 1965 have been phenomenal, beating the market handily and most of the other investment alternatives from an active management perspective (i.e. mutual funds and hedge funds). Berkshire Hathaway is a multinational holding company and diversified conglomerate run by the investor, chairman, and CEO Warren Buffett (since 1965). Buffett is a famed value investor. Berkshire Hathaway has created a significant legacy and impacted many investors over the last 60 years.
If an investor started in 1983 by investing $100 in Berkshire Hathaway stock, they would have compounded growth by 18% annually, significantly outperforming the market by roughly 900 bps per year.
Berkshire Hathaway has a higher Sharpe ratio than any stock or mutual fund with a history of more than 40 years – Truly remarkable!
As you will note in Table 1, outperformance has narrowed over time as Berkshire Hathaway has significantly grown in size, and this size reduces its pool of investable companies.
Table 1 – Berkshire Hathaway vs the U.S. Market Returns – 1983 to 2022
While we sat through the Berkshire Hathaway Annual Shareholders Meeting recently we began to think, about the two leaders – Warren Buffett (age 91) and Charlie Munger (age 98) as they are towards the end of their life’s journey have bestowed so many lessons over time.
Buffett/Munger are both still sharp as tacks, yet no one knows when the last Buffett/Munger-led Berkshire meeting will be. When asked about his succession, Buffett didn’t focus on the inner workings of the board of directors, the voting power of the shareholders, or even the strategy of the investment team. Rather, he talked extensively about the Berkshire culture almost as an embodiment of his values that will carry on even after he and Munger are gone.
This got us thinking, about how we could try to understand their methods overtime to try to systemize their approaches that survive well beyond their natural lives and try to clone their collective actions over time through quantitative models that capture their actions over a long period.
What we have found is that we believe that Buffett/Munger have captured many factor anomalies (Quality, Low Volatility, and Value) before anyone had “discovered them”, sector tilts, and through the use of leverage/liquidity and thoughtful risk-taking and has been compensated for taking on risk, outperforming market cap indexes and many mutual funds/institutional investor over time. These factor anomalies are connected to behavioral biases/psychology that is exhibited by investors. “Behavioral finance” literature is the study of how human behavior interacts with markets and suggests that investors exhibit behavioral biases due to cognitive or emotional weaknesses.
Examples include chasing winners, over-reacting, overconfidence, preferring “familiar” investments such as securities of the companies they work for or the country they live in (“home bias”), and myopic loss aversion. Markets at times are driven by emotions including these behavioral biases.
We have tried to decompose Berkshire Hathaway’s investment results between factor anomalies, sector tilts, and leverage, so that we understand the types of risks taken to drive the returns so that our clone funds may emulate the principles in a largely passive portfolio of ETFs via systematic risk associated with factor anomalies and sector tilts, as human behavior tends to repeat over history and did not want to rely on individual stock picking behavior.
As we have mentioned in our prior posts, markets are influenced by human behavior and we aim to create quantitative strategies that model this behavior before it occurs, so that we are able to profit from it.
We will review the following sections in today’s post:
Background on Berkshire Hathaway – Private vs Public Companies
Key Lessons from Buffett/Munger
Buffett’s Alpha – A review of AQR’s factor model
BT BRK Clone – Cloning through ETFs
1) Background on Berkshire Hathaway – Private vs Public Companies:
Berkshire Hathaway was originally a textile manufacturer, but now owns or holds controlling interests in dozens of big companies including Fruit of the Loom, Kraft Heinz, Benjamin Moore, Geico, Dairy Queen, and more.
Berkshire Hathaway originally (and still today) holds a lot of insurance companies, including National Indemnity Company and National Fire & Marine Insurance Company (now a part of National Indemnity), acquired in 1967, as well as Geico, acquired in 1996. Berkshire Hathaway owns or has a large stake in dozens of big companies, including public and private companies.
There are two components when it comes to analyzing Berkshire as a company:
A) 100% owned private operating companies where their financial statements are fully consolidated into BRK’s statements and thus their earnings are fully reflected in Berkshire’s results.
Main private businesses disclosed by Berkshire include:
Insurance and Reinsurance Businesses
Railroad (Burlington Northern Santa Fe)
Utilities and Energy (Berkshire Hathaway Energy)
Manufacturing and retailing (largely consumer staples)
B) Public Company equity holdings where only the dividends are reflected in Berkshire’s financial statements within the insurance income which included about $5B in 2021. We note that only ~30% of total earnings are paid out via dividends and the total ownership stake associated with earnings is not included in Berkshire’s financial statements. Mark-to-market changes in securities prices from quarter to quarter are included in Berkshire’s financial statements.
Table 2 – Total Earnings Available to Berkshire Hathaway – Public Securities vs Private Business Units
In Table 2, we note that as Berkshire has become larger, the securities portfolio has become a smaller proportion of total earnings, representing about 20% currently when looking at dividends provided by portfolio companies. Berkshire runs a concentrated portfolio as the Top 5 positions in the public securities portfolio, representing about 80% of the dividends and the total securities portfolio beta is consistent with the market at 1. Generally, there are no targeted allocations by investment type or attempts to match investment asset and insurance liability durations. However, investment portfolios have historically included a much greater proportion of equity securities than is customary in the insurance industry.
As Berkshire has increased in size, there has been a larger contribution coming from full consolidated private businesses ~80% of the total earnings as more excess cash provided by “float” or existing business operations is redeployed to full acquisition of businesses (i.e. taking public companies private).
We note that total potential earnings inclusive of total stake ownership of earnings within each company in the securities portfolio would represent about $44B, putting Berkshire’s Price-to-earnings ratio at 17.5 times (which is lower than the S&P 500). To put Berkshire’s earnings size and diversification into context, the largest company in the world (Apple) earns about $100B annually and Berkshire’s ownership stake is about 6% of Apple.
There are high returns on invested capital of almost 8% when considering consolidated private companies and earnings rather than dividends of the public company companies of the securities portfolio.
Berkshire has focused on companies in defensive industry sectors with high-free cash flow, high quality as they have a large moats, and low volatility including:
Consumer staples (Manufacturing, Service, and Retailing),
Utilities, Financials, Health Care, and Transportation (Railroads).
2. Key Lessons from Buffett/Munger
There have been numerous books and articles about lessons from Buffett/Munger over the 60 years of Berkshire that recount the numerous lessons. Below we have offered a summary to provide context around the decomposition of Berkshire’s returns.
We believe investors can take the following away which have led to Buffett’s success over time:
Investing in Factor Anomalies that persist over time:
An unconstrained investment style (able to go long/short and use leverage including derivatives)
Act Greedy when others are Fearful (buy a company at a value below intrinsic value – the Value Factor Anomaly)
“It’s far better to buy a wonderful company at a fair price than a fair company at a wonderful price” (Buy high-quality companies for a fair price moving away from the deep value/cigar butt investing style of his mentor Benjamin Graham – the Quality Anomaly)
Invest in companies with wide moats (extremely high returns on assets and capital) Buffett has detailed the many common attributes of these companies, and a few of them are as follows:
They see their profits in cash.
They are not natural targets of competition.
They have the freedom to price their products.
They are understandable.
They do not take a genius to run.
They earn very high returns on capital and assets.
These companies tend to be low volatility equities as their performance is consistent and boring.
2) Leveraging Permanent Sources of Capital by cultivating long-term high-quality shareholders and superior capital allocation skills:
Permanent capital is required for the buy-hold long-term strategy of investing in factor anomalies based on low volatility, high quality, and value, based on a levered strategy. These factor premiums-to-market could not be earned if the capital was transitory.
Buffett courted quality shareholders by providing informal education, mainly through an acclaimed annual letter and legendary annual meetings. By these means, Buffett taught the fundamentals of business and investing, such as moats and circles of competence.
He also conveyed the special Berkshire’s special features to this group, especially the concepts of partnership and permanence.
This enabled shareholders’ equity to be permanent and Buffett would not have to liquidate his portfolio strategy at the most inopportune time, say a significant market drawdown or significant underperformance of a benchmark.
By educating investors to focus on buy-hold superior long-term capital growth rather than demanding Berkshire to return capital in the form of short-term dividend income, and short-term capital gains, has allowed for capital within the group of businesses to compound uninterrupted and redeployment into further high cash flow/high-quality businesses, growing the size and diversification of Berkshire over time. Historically, Berkshire has not returned capital to its shareholders through dividends or buybacks consistently, therefore not creating an ongoing capital obligation. From time to time Berkshire has repurchased or bought back its shares, but this is usually when Buffett considers that the market price of shares is lower than the “intrinsic value” of Berkshire, therefore benefitting shareholders. This is the same framework he’s used for acquiring a business and public company shares over his career.
Establishing the business around the insurance float business as a means to compound capital over time by using other people’s money or leverage to grow the size of the permanent capital base for investment, rather than solely relying on the free cash flows of existing businesses to acquire new businesses. Buffett has continued to use leverage to magnify the returns on lower-risk equities and maintained his operating principles over time and continues operating at high risk even after experiencing some ups and downs that have caused many other investors to rethink and retreat from their original strategies.
Float is the money that a business receives today but doesn’t have to pay out until sometime in the future. Float is most commonly seen in insurance companies with customers paying premiums upfront to insure themselves against bad things happening sometime in the future. A dollar you receive today is worth more than a dollar you get a week from now because you can invest it at some rate to receive more money in the future. Buffet realized that the more float he had, the more float he could invest to buy other businesses.
The final step was increasing the duration of time between when the premiums are received and when they are finally paid out. So, for Buffett, this meant buying up longer-tailed insurance companies like an insurance for catastrophes, and recently, Reinsurance companies – which may be low a probability but high impact events. Insurance companies also will maintain high-credit quality and high credit ratings, which enables them to raise debt at low costs relative to lower credit quality issuers.
Also, Buffett has discussed while the business model may be levered, having loads of liquidity (cash and US treasury bills), though is a small cost to pay bear though, lets them sleep well. Moreover, during the episodes of financial chaos that occasionally erupt in the economy, they will be equipped both financially and emotionally to play offense while others scramble for survival. We cover this concept later on.
3) Decentralized Management Structure
While many public corporations implemented strict controls and oversight mechanisms to ensure management performance and regulatory compliance, Berkshire Hathaway moved in the opposite direction. The company had only two main requirements for operating managers: submit financial statement information every month and send free cash flow generated by operations to headquarters.
Management was not required to meet with executives from corporate headquarters or participate in investor relations meetings; nor was it required to develop strategic plans, long-term operating targets, or financial projections. Instead, local managers were left to operate their businesses largely without supervision or corporate control.
3) Buffett’s Alpha – A Review of AQR Capital’s factor model
AQR Capital’s model and analysis have been the most complete analysis of sources’ of Berkshire Hathaway’s return over time via many well-known factor anomalies that have persisted over time.
Before we jump to AQR’s model and analysis, let’s spend a few moments discussing factor investing and the sources of these returns which have been covered in academic studies over time. A number of these factor anomalies are covered in Capital Asset Pricing Model covered by Fama and French and other studies have expanded the original CAPM over time.
The CAPM (Capital Asset Pricing Model) explains that an asset’s expected return should be comprised of a risk-free rate and a return associated with a market premium. In the CAPM, securities have only two main drivers: systematic risk and idiosyncratic risk. Systematic risk in the CAPM is the risk that arises from exposure to the market and is captured by beta, the sensitivity of a security’s return to the market.
Since systematic risk cannot be diversified away, investors are compensated with returns for bearing this risk. In other words, the expected return to any stock could be viewed as a function of its beta to the market and/or the risk factor premium.
The market premium represents the risk associated with movements in the overall market (something that cannot be diversified away, as it affects all assets in the universe).
The CAPM is defined as:
In general, a factor can be thought of as any characteristic relating to a group of securities that is important in explaining their returns and risk. As noted in the early CAPM-related literature, the market can be viewed as the first and most important equity factor. Beyond the market factor, researchers generally look for factors that are persistent over time and have strong explanatory power over a broad range of stocks.
Risks associated with factor anomalies such as small size, value, low volatility, momentum, and quality cannot be diversified away either. Assets that move closely in unison with this excess market risk will achieve higher returns than assets that do not.
Table 3 summarizes six of the most widely studied factor anomalies. More recently, Low Volatility, Yield, and Quality factors have become increasingly well-accepted in the academic literature.
Table 3 – Systematic Factor Anomalies from the Academic Research
What It is?
How is it measured?
Captures excess returns to stocks that have low prices relative to their fundamental value
Book to price, earnings to price, book value, sales, earnings, cash earnings, net profit, dividends, cash flow
Higher real or perceived risk (business cycle risk) Loss aversion and mental accounting biases
Low Size (Small Cap)
Captures excess returns of smaller firms (by market capitalization) relative to their larger counterparts
Market capitalization (full or free float)
Incorrectly extrapolating the past into the future
Reflects excess returns to stocks with stronger past performance
Relative returns (3-mth, 6-mth, 12-mth, sometimes with last 1 mth excluded), historical alpha
Overconfidence, self-attribution, conservatism bias, aversion to realizing losses Under reaction and overreaction
Captures excess returns to stocks with lower than average volatility, beta, and/or idiosyncratic risk
Standard deviation (1-yr, 2-yrs, 3-yrs), Downside standard deviation, standard deviation of idiosyncratic returns, Beta
“Lottery effect” overpay for high volatility stocks and underpay for low volatility stocks due to the “irrational” preference for volatile stocks. Leverage aversion
Captures excess returns to stocks that have higher-than-average dividend yields
Captures excess returns to stocks that are characterized by low debt, stable earnings growth, and other “quality” metrics
ROE, earnings stability, dividend growth stability, strength of balance sheet, financial leverage, accounting policies, strength of management, accruals, cash flows
Source: MSCI Foundations of Factor Investing
In addition to historically exhibiting excess returns above the market, an equally important rationale for factor investing is the wealth of evidence that they can account for a significant portion of fund returns and institutional active fund returns.
In the next section, we note that AQR Capital’s paper has tried to determine how much of Berkshire’s active returns relative to the benchmark have been a result of investing in these factor anomalies versus stock-specific outperformance via superior securities selection.
Buffett’s portfolio and performance can be understood using these factors:
Has unique access to leverage
A disciplined approach to high quality, low-risk stocks may generate strong risk-adjusted and absolute-returns
Short sells options
Buffett utilizes debt in a very judicious and strategic fashion.
Buffett understands the inherent value in his investments, so he does not allow market fluctuations to control his emotions.
Buffett creates wealth and takes on leverage because he maintains high levels of liquidity.
Warren Buffett’s large returns come from both his high Sharpe ratio and his ability to leverage his performance to achieve large returns at high risk. While Buffett is known as the ultimate value investor, we find that his focus on safe quality stocks may be at least as important to his performance. Leverage has appeared to magnify returns of these safe quality stocks and enable strong growth in capital over time.
So Buffett uses leverage to magnify returns, but how much leverage does he use?
Berkshire Hathaway’s insurance float represents about 50% of its liabilities. Collecting insurance premiums upfront and later paying a diversified set of claims is like taking a “loan.”
This is very similar to how a bank makes money from demand deposits (borrowing money in the short-term that can be redeemed at any time) as well, by making long-term loans on properties backed by collateral (“low risk”), which is known as running a maturity mismatch risk. Runs on banks may occur from time to time, but Buffett appears to be a strong balance sheet manager holding ample excess liquidity which may be deployed in times of crisis for lower valuations for high-quality companies as compared to intrinsic value.
Over the period of 1994 to 2022, Berkshire’s insurance float grew at a compound annual rate of 14% per year, which compares to annual growth in Berkshire Hathaway’s stock price of ~13% and investment portfolio of ~12% over the same period.
Other businesses that produce float include:
Insurance and Pension Funds – funds collected upfront and paid out later
Retail Banks & Brokerages (Wells Fargo, Bank of America)
Subscription and Pre-paid Contracts/Negative Working Capital (Netflix, Coca-Cola)
You will notice that Berkshire has historically invested in these types of businesses as well given the high returns on capital.
Berkshire sells derivatives, which serve as both a source of financing and a source of revenue.
In Table 4, we observe that Berkshire’s cost of liabilities has been very low over time, even relative to US Government yields as debt has been raised at a negative spread (assuming an average duration of 10-years for the liabilities).
We note that over the past 40 years, we have also enjoyed a bull market in bonds as interest rates have fallen significantly and the focus on the wealth effect, has significantly benefited levered players in the process, including Berkshire Hathaway, as assets repriced higher due to lower costs of capital.
Table 4 – Cost of Leverage and Amount of Leverage in Berkshire Hathaway Business Model
Being able to repeat this method in today’s relatively low-interest-rate environment may be very difficult. He has stuck to a good strategy—buying cheap, safe, quality stocks—for a long period, surviving rough periods where others might have been forced into a fire sale or a career shift, and he boosted his returns by using leverage and maintaining liquidity for buying opportunities when the equity market dives.
We estimated that Buffett applies a leverage of about 1.6 to 1, boosting both his risk and excess return in that proportion. As a result of the leverage, he has also managed to hold a significant amount of liquidity as well over time which is very important to levered businesses in large drawdowns, as well as deploying it when stock valuations of high-quality businesses are beaten down.
The focus on maintaining a stable level of liquidity is critical as many have been caught by seeing asset prices rise and thinking of the added cost of maintaining a liquidity buffer is taking away from returns and reducing this buffer at the most inopportune time– see Table 5. You can see that Berkshire positioned itself ahead of the Financial Crisis of 2008-2009 to have significant liquidity to deploy into value opportunities that were trading below their “intrinsic value”, despite the added cost of maintaining a higher liquidity buffer.
Table 5 – Liquidity in Berkshire Hathaway Business Model
In its study of Buffett’s performance, AQR reviewed several factor anomalies and regressed the performance of Berkshire stock and its equity portfolio performance (via 13F reports).
This is a common way to measure the performance of a portfolio manager to determine the Alpha (positive return relative to a benchmark) due to security selection, rather than beta due to factor anomalies/tilts in the portfolio.
AQR publishes its factors every month. Based on these factors, we re-performed the regression study using more current data (as the paper was based on data from 1976 to 2017) on both Berkshire Hathaway’s shares outstanding and Berkshire’s Public U.S. stocks (from 13F filings) to determine which of the following factors had the greatest impact. AQR’s Regression to determine Buffett’s exposures:
In Table 6, we summarize these factors and the Berkshire Regression Factor Loadings.
Table 6 – AQR Regression Factors Anomalies
Berkshire Factor Loading
Buying stocks of high book value to market value while shorting stocks of low book value to market value.
Positive loading thus reflects a tendency of buying cheap stocks
Low Size (Small Cap) (SMB)
Long small-capitalization stocks and short large-cap stocks
Negative loading reflects BRK’s tendency to buy large-cap stocks
Buying stocks that have performed well relative to peers over the past year (winners) while shorting the stocks that are relative underperformers (losers).
Insignificant loading on UMD means that Buffett is not chasing trends
Low Volatility/Bet-against-Beta (BAB)
Bet-against-Beta (BAB) factor is simply a long-short portfolio that buys stocks with low market beta (lowest 10%) and sells stocks with high market beta (highest 10%).
Exposure to the BAB factor and Buffett’s unique access to leverage is consistent with the idea that the BAB factor represents the reward for the use of leverage
Quality minus Junk (QMJ) factor buys companies that are profitable, safe, and have high payout (top 30%), and sells companies on the other end of this quality spectrum (lowest 30%)
BRK’s tendency to buy high-quality companies—that is, companies that are profitable, growing, and safe and have high payout
Looking at each of the factors in Table 7, we note that Quality and Low Volatility (Beta Against Beta – BAB) have provided significant premiums to market returns, relative to other well-known styles such as Value, Momentum, and Size. We note that despite many investors investing in these styles, these anomalies have persisted over time calling into question the Efficient Market Hypothesis.
You can also see that factors such as Value and Momentum tend to be negatively correlated as the Value style will be a buy as the Momentum style breaks trend, typically when global liquidity is reducing.
Quality and Size are negatively correlated as smaller companies may be more levered to the business cycle and not all will survive to become large-cap high-quality companies.
Berkshire’s investing philosophy has focused on long-term investing in cheap/quality/low-volatile stocks through the business cycle which has allowed it to generate significant premiums relative to the market.
Table 7 – AQR Factors – 1972 to 2022 – Factor Return Premium to Market
This may suggest that human emotion/behavior biases are inherent within institutional investors’ investment policy statements (i.e. many investors are long-only and not able to use leverage). Also, Bet-against-Beta’s high return may suggest that institutional investors that are not able to take on leverage to magnify returns of low volatility securities to beat their benchmarks, may bid up the price of high beta stocks as they require high unlevered returns, which eventually reduces the return premium of high beta assets. When a majority of market participants face leverage constraints, they may acquire more high-beta stocks to achieve a target exposure to market risk or a target return volatility.
Beowulf Treasury’s Roll-Forward of AQR’s Study to 2022
Below in Table 8, we have used a rolling regression over 36 months to try to quantify Berkshire’s and Berkshire’s equity portfolio exposure to the various factors of systematic risk as we have reviewed above. As Berkshire Hathaway is levered 1.6-to-1, we have reduced the stock price changes impact associated with leverage, to make returns comparable to unleveraged factors.
In Table 9, we show the factor tilts on Berkshire’s stock and notice that the largest exposures over time are Value, BAB, and Quality. Value and Quality are expected, given Buffet’s noted style. We also note that very little alpha due to security selection appears to have been generated and much of Berkshire’s outsized returns are largely due to factor-betas and leverage. This is consistent with the original paper.
We have noted that some practitioners have raised a few issues with the Beta against Beta construction. In their study “Betting against Betting against Beta” (BABAB), published in the January 2022 issue of the Journal of Financial Economics, Robert Novy-Marx, and Mikhail Velikov re-examined the performance of the betting against beta factor. They began by noting that the authors used unconventional procedures to construct their factor, which Jack Vogel also covered in his review of BAB here.
Their main critique of the betting against beta paper was that its construction methodology results in an equal-weighting strategy instead of the conventional market-cap weighting (and thus ends up with large positions in very small-cap stocks with high transaction costs).
There have also been discussions around BAB being regime dependent on either a value or growth regime. In our research, we note that generally higher levels of growth of global liquidity tend to be associated with growth regimes that benefit High Beta stocks vs. value regimes that tend to be lower growth of global liquidity which benefits Low Volatility stocks.
Despite this, we believe the discovery of the long low beta/short high beta anomaly is something we could look to implement.
Table 8 – Berkshire Hathaway’s shares outstanding and Berkshire’s Public U.S. stocks (from 13F filings)
Table 9 – Average Factors Weights – 1981 to 2022
So it appears that Berkshire Hathaway’s secret to success is the early identification of these factor anomalies and strategic use of leverage to magnify returns, especially in a period of declining interest rates/lower cost of funding over the past 40 years.
In our review, to be able to mimic the BAB factor to get the same factor-beta as Buffet/Berkshire would create significant implementation issues for most individual investors. Buffett has had unique access to leverage and remained liquid during downturns to potentially take advantage of situations by buying up undervalued stocks that his competitors potentially would not have been able to take advantage of as they had been previously liquidated via investors redeeming due to poor relative performance. His courting of long-term shareholders to provide permanent capital and partnership and related education has supported his strategy.
We wonder, is there another way to take advantage of the behavioral bias that Beta-Against-Beta has uncovered?
As not everyone would have the unique access to leverage or significant multiples of permanent capital relative to personal capital, what could an individual investor do?
What if we could tactically invest in times when High Beta and Momentum get bid up by institutional investors that are incapable of following Buffett’s buy-hold leveraged low volatility strategy to beat the benchmark due to leverage constraints?
In the next section, we cover how we may be able to leverage some of the learnings such as:
Investing in Low Volatility/Quality stocks via ETFs
Strategic use of Leverage and Liquidity
Does the Long-Short portfolio strategy outperform Trend Following for individual investors?
Could we use Tactical Trend Following to take advantage of the Bet-Against-Beta anomaly?
Does Trend Following Factor Momentum Persist over time and potentially outperform buy-hold or long-short portfolio?
We have tested our Trend Following Wave Runner Framework from the previous post on global assets on the AQR Capital factors to see if trend following Factor momentum persists over time. See the prior post for further details on the methodology of our Risk Indicator.
The underlying economic justification for trend following rules lies in behavioral finance tenets such as those relating to herding, disposition, confirmation effects, and representativeness biases. At times information travels slowly, especially if assets are illiquid and/or if there is high information uncertainty; this leads to investor under-reaction. If investors are reluctant to realize small losses then momentum is enhanced via the disposition effect.
Trend Following – Factor Anomalies (AQR factors) x Wave Runner Portfolio
We have constructed the trend following portfolio using AQR’s factors combined with BT’s Risk Indicator. What this means if say the Value, Quality, and Low Volatility factor has outperformed on a relative basis the other factors based on weighted 1-mth, 3-mth, 6-mth, and 12-mth (13612W) and the Global Risk Indicator are positive (i.e. above-trend growth of business/liquidity cycle), invest 40% in the top 2 and 20% in the 3rd ranking factor.
In Table 10, the Trend Following strategy paired with the BT Risk indicator would have outperformed the US Market by 240 bps and unlevered BRK-A by 150 bps per year. By using the same level of leverage ($1.6 of debt to $1 of equity), the BT Factor Wave runner would have outperformed BRK-A over the period.
However, we note that AQR factors are not investable at this time so we will cover how we may implement this in the next section.
Table 10 – Trend Following on AQR Factors vs Berkshire Hathaway
So how could we turn this research into a sustainable portfolio strategy to implement for individual investors? Rather than trying to pick the right stocks that may be industry leaders as Buffet has done over time, we may be able to ride factor and sector betas that mimic Buffet’s allocation over time.
We are going to review the following factor ETFs as we have reviewed them relative to the AQR factors we covered in Section 3 and run similar rolling regressions to determine our monthly allocation to each factor to mimic Berkshire/Warren Buffet’s position.
In Table 11, we have selected ETFs based on single MSCI factor indexes and backtested against the AQR factors to ensure that each ETF largely represented the factor that is it supposed to. You will note that each ETF has the strongest loading to the AQR factor, however, there is some crossover into other factors as High Dividend Yield and Min Vol have some cross-over to the Value factor loading, though VLUE ETF has the strongest Value component. The R-squares for each are all greater than 0.75, which suggests that the factor returns generally explain a lot of the variation in returns over time.
Table 11 – ETFs Factor Loadings based on AQR Factors:
Table 12: Summary of Backtests – BRK Clones and Trend Following Portfolios
In Table 12, we note that Rolling Regression models over the period have largely kept up with Berkshire Hathaway on an unlevered basis and have a higher Sharpe ratio. The trend-following model (BT Factor Anomalies x Wave Runner) has outperformed all portfolios and has had lower drawdowns. This is significant as we have not used leverage to magnify returns of the factor anomalies. We will review this model later on. We have for comparative purposes included the BT Momentum and BT Wave Runner which are trend following portfolios on global assets, and have outperformed all portfolios as Sharpe Ratios are largely above 1.
Rolling Regression Models:
We have used a rolling regression over a 36-month period to try to quantify Berkshire’s stock to the various factors of systematic risk as we have reviewed the above Factors (Low Volatility, High Dividend Yield, Value, Momentum, Quality, and Equal-weighted) as well as Industry Sectors (Consumer Staples, Technology, etc.) against Berkshire’s Stock and Berkshire’s Equity Portfolio to determine the factor/sector betas of Berkshire Returns.
With this methodology, we are essentially mimicking Buffett’s stock picks on a systematic factor basis on a rolling 36-mth basis, without taking a specific bet on a single stock, as we have seen in section 2, much of Buffett’s market outperformance has been his superior selection of factor anomalies.
A) BRK Clone–Factor Anomalies Regression Model
In Table 13, we have reviewed the Factor model. This Factor Model is based on regressing factor anomalies ETFs against Berkshire stock, to determine factor loadings to each of the factor anomalies. This model was not constrained to the long-only portfolio, allowing it to go long and short ETFs similar to Berkshire exposures over time.
Table 13 – BT BRK-Clone Factor Anomalies Model vs Unlevered BRK and US Market
B) BRK Clone – Industry Sector Model
In Table 14, we have reviewed the Industry model. This Industry sector Model is based on regressing factor anomalies against Berkshire stock, to determine factor loadings to each of the sectors. This model was not constrained to a long-only portfolio, allowing it to go long and short ETFs similar to Berkshire exposures. We note, that this portfolio is quite volatile.
Table 14 – BT BRK-Clone Industry Sector Model vs Unlevered BRK and US Market
Trend Following Model – BT Factor Anomalies Model x Wave Runner:
So we mentioned earlier that we potentially could we leverage the research done on the Bet-against-Beta research on a tactical basis by capitalizing on the behavioral anomaly noted that institutional investors that are leveraged constrained tend to bid up high beta/momentum stocks to outperform their benchmarks. We suggest that the BT Factor Anomalies Model does exactly this – capitalize on this behavioral bias by participating in business/liquidity cycle upswings in these types of stocks, and tactically moving to safe assets as the growth rate of the business/liquidity cycle slows.
We have used the same methodology using the Trend following methodology, paired with the Global Risk Indicator similar to what we would have done in Section 3 with AQR Capital’s Factor anomalies. AQR Capital’s Factors are based on customized portfolios which may be difficult to replicate for individual investors. With this model, we have utilized investable ETFs available for all individual investors – see Table 15 for more information on the ETFs.
For example, this model would consider if the Value, Quality, and Low Volatility factor has outperformed on a relative basis the other factors based on weighted 1-mth, 3-mth, 6-mth, and 12-mth (13612W) and the Global Risk Indicator are positive (i.e. above-trend growth of business/liquidity cycle), invest 40% in the top 2 and 20% in the 3rd ranking factor in risk-assets which are the Factor ETFs. If the Global Risk Indicator is negative, the portfolio will invest in the Safety Asset portfolio based on relative momentum based on weighted average returns of weighted 1-mth, 3-mth, 6-mth, and 12-mth (13612W) – See Table 17 for more information on the Safety portfolio and Global Risk Indicator.
The BT Global Risk Indicator is a proprietary index based on several factors both Market Sentiment and Fundamental that we equally weight: 1) High Yield Credit Spreads 2) VIX term spreads 3) OECD composite leading indicator, 4) Global Liquidity Index 5) US Housing Starts 6) High Beta Currencies vs Low Beta Currencies 7) Copper and Gold Ratio.
Table 15 – Factor ETF and Inclusion Criteria
In Table 16, we summarize the simulation of BT Factor Anomalies x Wave Runner Portfolio (unlevered) since 1993 has been on par with Berkshire Hathaway Returns as stated (based on 1.6x leverage) and significantly outperformed the market over the period and separate sub-periods.
We note that higher risk assets/higher return assets (momentum, high beta, small size) tend to have large outperformance to market when the global risk indicator is signaling risk-on – see Table 18.
The portfolio is allocated to a greater extent to these higher-risk assets during the risk-on period which tends to benefit from higher than trend liquidity conditions, resulting in higher returns. These high-risk assets are particularly susceptible when liquidity conditions are tightening or below trend, as we note in Table 18.
However, as the portfolio tactically moves into the safety portfolio (safe assets) when the Global Risk Indicator is risk-off protecting our capital base as the large drawdowns associated with these high-risk assets do not impact the portfolio. We have summarized our Global Risk Indicator and average allocations to each of our Safety Assets in Table 17.
Table 16 – BT Factor Anomalies Model x Wave Runner vs Unlevered BRK and US Market
We note that in risk-off periods when liquidity conditions are tightening or below trend which represents about 46% of the 1993 to 2022 period when the portfolio is in safe assets, Quality and Low Beta ETFs outperform the market-cap-weighted index by 4.4% and 2.4% respectively. As a result, we expect Berkshire to outperform during these periods and tend to be when they deploy more excess liquidity to market opportunities in the Value spectrum (value is below intrinsic value).
Table 17 – BT Global Risk Indicator and Safety Assets used in Risk-off Periods
In Table 18, we note that on a relative basis Min Vol, Quality, and Low Beta provide relative protection versus other equity factor strategies and market-cap indexes. We did calculate the inclusion of Low Beta, Min Vol, and Quality in the Safety Portfolio when the Global Risk Indicator was in a Risk-off position but did not consider the impact on the overall portfolio returns and volatility to be significant enough for inclusion in the Safety Portfolio.
The Trend Following Factor Anomalies strategy optimizes return vs risk, in this backtest period relative to Berkshire without taking on single stock risk and remaining very diversified over the period, and does not take leverage on and achieves a better Sharpe ratio at 0.91 versus Berkshire Hathaway at 0.67. Returns are comparable to Berkshire’s returns of 12.5% which relies on leverage of 1.6x-to-1.
We believe, that the Trend Following Factor Anomalies portfolio capitalizes on the following investment behavioral anomalies we have discussed previously:
As we noted earlier the Bet-Against-Beta (BAB) factor, institutional investors that are not able to take on leverage to magnify returns of low volatility securities to beat their benchmarks, may bid up the price of high beta stocks as they require high unlevered returns, which eventually reduces the return premium of high beta assets. When a majority of market participants face leverage constraints, they may acquire more high-beta stocks to achieve a target exposure to market risk or a target return volatility. This portfolio rides the momentum wave as the business/liquidity cycle is on the upswing. As we mentioned earlier, the “Lottery effect” forces investors to overpay for high volatility stocks and underpay for low volatility stocks due to the “irrational” preference for volatile stocks.
There have also been discussions around BAB being regime dependent on either a value or growth regime. In our research, we note that generally higher levels of growth of global liquidity tend to be associated with growth regimes vs. value regimes which tend to be lower growth of global liquidity.
By splitting the portfolio’s investment allocation between Risk-on (Growth-regime) and Risk-off (Value-regime) on a tactical basis based on our Global Risk Indicator, the portfolio takes advantage of trends on a relative basis as the extrapolation of the recent past into the future by investors is significant across many studies. The Global Risk Indicator reduces the drawdown risk of the portfolio before the correction of investor expectations occurs which reduces the value of higher return/risk factors anomalies (high beta, small size, momentum).
Given that volatility of this BT Factor Anomalies x Wave Runner strategy of 14% is lower than Berkshire Hathaway’s of ~19%, we could potentially use leverage strategically during risk-on periods, to lever up to say 1.34x-to-1 so that we could match Berkshire’s volatility of 19%, which potentially magnifies returns to above 17% (higher than Berkshire’s returns of 12.5% over the period), though could increase drawdown to 32% (still below Berkshire’s 44%). So by adding leverage to the BT Factor Anomalies portfolio, annual returns would be roughly 400 bps more than Berkshire Hathaway over the simulation period.
Brokerage firms can establish their own rules for how much leverage they allow to be placed when their clients’ trade and how much collateral must be on hand. However, the Federal Reserve Board established Regulation T which requires at least half of the purchase price of a stock position to be on deposit (leverage ratio of $2 of assets per $1 of equity), so this strategy may be practicably implemented by individual investors.
Table 18 – Average Allocation Risk-on Periods and Factor Returns Premium to Market
Table 19 – Drawdowns by Factor during Risk-on and Risk-off Periods (1991 to 2022)
5) Conclusions: So what can we conclude from this analysis?
Table 20: Summary of Backtest Period (1993 to 2022)
Berkshire Hathaway has created a significant legacy and impacted many investors over the last 60 years. There have been many lessons over the years. Strategic use of leverage to magnify returns of cheap, high-quality, and low beta equities, along with ample liquidity in a buy-hold strategy over the long term has been a centerpiece of Berkshire’s strategy. Buffett/Munger appears to have “discovered” these factor anomalies/risk premium earlier than most investors and stuck to this strategy while cultivating permanent capital through the informal education of investors that did not demand short-term capital returns through dividends and buybacks. This allowed for capital to be compounded at a significant rate in an economy that relies on the ‘wealth effect’ to drive forward consumption to drive economic growth. Factor anomalies have a basis in investor behavior/psychology, even in algorithmic trading strategies which may persist going forward despite trading/investment decisions being outsourced to computers.
Trend Following based on trailing momentum of 13612W and BT Wave Runner strategy when combined with Factor Anomalies exposure may provide an optimal risk vs return portfolio when compared to Berkshire Hathaway’s portfolio returns on an unlevered basis, as the Sharpe ratio of Factor Anomalies x Wave Runner portfolio of 0.91 is greater than 0.67 of Berkshire Hathaway.
We note that BT Factor Anomalies x Wave Runner portfolio uses tactical allocation to higher return/risk factor anomalies (high beta, momentum, small size) which capitalize on institutional investor constraints against using leverage and over-indexing on high beta to beat the market-cap-weighted indexes.
We note that the tactical asset allocation we have described may not be available to all individual investors, and may be too concentrated and too time-consuming in implementation.
We note this is a very different strategy as compared to Berkshire’s buy-and-hold of low volatility, high-quality and cheap equities on a 1.6x levered basis strategy which may not be available to all individual investors, and have therefore outsourced capital allocation, and leverage decisions to Berkshire, by buying their stock. However, we do note that the strategies take advantage of investor behavioral biases which have historically persisted over time. We believe that these strategies are two sides of the same coin so to speak.
Institutional Investor Policies based on a largely fully invested strategic asset allocation bands, lack of leverage use, and constraints against short positions may not allow for the flexibility required to implement either strategy we have discussed in this post.
We plan to monitor the 3 Trends following strategies we have covered in our previous two posts as summarized in Table 20, going forward on this website every month.
We also plan to determine if the inclusion of factor anomaly ETFs from other jurisdictions may reduce the risk or/and enhance the return of the US-only-Factor Anomalies portfolio.
Our last post got us thinking about how difficult it must be for individual investors to stick to a portfolio strategy and drown out the noise given the recent news about inflation, interest rates, and Russia/Ukraine war and calls for a potential recession or even stagflation.
So we set out to create a systematic trend following portfolio strategy based on academic and practitioner investment research that would work well in any market or economic regime (based on simulated historical analysis) and would allow investors to potentially make money in any environment by using both fundamental and sentiment indicators to help position portfolios to ride the waves of liquidity and momentum.
These portfolio strategies build upon the posts we have previously published that show how our opinions and views may be executed to provide tangible value over time.
We will cover the following topics in today’s post:
Introduction to Momentum/Trend-following Investing
BT Wave Runner Risk Composite Indicator – the components
BT Global Liquidity Index
OECD Composite Leading Indicator
U.S. Housing Starts
High Yield vs US Treasuries
High Beta vs Low Beta Currency
We believe that trend-following/tactical asset allocation portfolio strategies provide great risk-return trade-offs and offer a significant improvement in terms of risk-adjusted returns over static asset allocation portfolio strategies. We evaluate 2 portfolios (BT Momentum and BT Wave Runner) based on simulated asset returns. To be included in the investment universe, the asset classes require a separate ETF to exist and are investable by individual investors.
The combination of fundamental and market sentiment data provides risk control when incorporated with momentum that has improved the risk-adjusted returns of portfolio strategy by riding the liquidity and momentum waves.
1) Introduction to Momentum/Trend-following Investing:
What is Momentum?
Momentum is the phenomenon that securities that have performed well relative to peers (winners) on average continue to outperform, and securities that have performed relatively poorly (losers) tend to continue to underperform.
Momentum is an investment style that has been studied extensively by academics for many years. AQR Capital Management has extensively researched momentum as an investment style and shown evidence for momentum is pervasive and supported by almost two decades of academic and practitioner research.
Studies have documented momentum in the U.S. as far back as the Victorian age. The evidence also shows that momentum works broadly across asset classes, including foreign stocks, bonds, commodities, currencies, index futures, and global country index selection. These studies are largely based on price returns and some fundamental considerations (i.e. earnings momentum).
So Why Does Momentum Work?
Momentum is driven by investor behavior: slow reaction to new information, asymmetric responses to winning losing investments, and the bandwagon effect/overreaction as short-term traders may use recent performance as a signal to buy or sell.
Momentum tends to persist for some time (6-12 months) before leading to reversals as too many investors pile in the same investments as prices become detached from fundamentals, causing volatility and drawdowns in asset prices.
Based on this excellent research, we wanted to see if we may apply it in a systematic way that may reduce investor behavioral biases (i.e. selling at the bottom of the market cycle or buying at the top). As we have noted in our research, investor risk appetite/behavior is a very significant factor in the results as measured through Household Balance Sheet Allocation to Equities (based on Flow of Funds position Accounts) and Margin Debt.
We have taken this research and applied it to ETF investing on a global basis looking at 64 ETFs/asset classes spanning equities, currencies, bonds, commodities, and Real Estate Investment Trust (REITs).
The idea is if you can maximize the investment universe, an investor may maximize their returns by catching a momentum wave in a particular asset class at a particular time (i.e. when the trend is your friend).
We have called this the BT Momentum strategy (a long-only strategy), which is a simple strategy of investing in the top 3 ETFs (weighting of 40%/40%/20%) each month based on prior month data using a momentum score called Fast Momentum (13612W) which we will discuss later on, starting with monthly asset class returns in 1985.
Each month the investor would sell the previous month’s investments and buy the 3 strongest asset classes based on the 13612W fast momentum filter for each, based on buying at the beginning of the month based on the prior month’s momentum signals.
This would lead to systematic buying and selling every month based on momentum signals. We have examined the portfolio statistics over the last ~40 years and split them into 4 different periods (roughly 10 years) to determine if there is persistence in returns as the research states. Given that trading is largely commission-free, implementing this strategy on a go-forward basis, we believe transaction costs should be minimal.
In Table 1, we show the results of the simulated portfolio starting with $100 (no further contributions) in 1985, which has multiplied to $28 million by end of 2021 based on compound annual returns of 40% per year, far outperforming the Wilshire 5000 by ~30% per year and 60% of the time on a monthly basis – which are very strong results.
The overall correlation of monthly results of the BT Momentum portfolio to US equity markets is low (0.32) over the period, thus providing some diversification to standard long-only heavily weighted US equity portfolios. These results are impressive indeed and appear that results are persistent across time.
Table 1 – Summary Results – BT Momentum Portfolio Strategy vs Wiltshire 5000 – 1985 to 2021 (monthly results)
However, the annual volatility of 40% of the BT Momentum strategy is far too much for most investors to stick with this strategy. Also, the BT Momentum portfolio strategy provides little drawdown protection relative to a buy-hold strategy of the Wilshire 5000 index (see Table 2).
Table 2 – Summary Results – BT Momentum Portfolio Strategy vs Wiltshire 5000 – 1985 to 2021 (monthly results)
We set out to try to reduce the annual volatility/max drawdown by using the BT Market Risk Indicator composition which identifies periods of economic and liquidity expansion, which we will cover later on in our Wave Runner Portfolio Strategy section.
Defining the Momentum Score
Typical momentum strategies use a trailing 12-month return or 10-month Simple Moving Average (SMA) to determine which asset classes may exhibit higher relative scores of momentum.
We do not use the traditional 10-month SMA filter in our analysis, but something slightly faster, the weighted variant of the well-known average return over the last 1, 3, 6, and 12 months, called Fast Momentum (13612W filter) which has been popularized by Wouter J. Keller on his website TrendXplorer.
Table 3 below shows how different momentum filters pick up monthly returns at a different paces. We note that the 13612W filter picks up about 70% weighting on the previous 3 months (bottom right corner chart). So the 13612W momentum factor picks up reversals in trend faster than other commonly used methods. We have used the 13612W momentum score within both the BT Momentum and BT Wave Runner portfolio strategies as well as Risk Composite Indicator.
Table 3 – Momentum Filter Comparisons
For inclusion in the investment universe, all asset classes require a separate ETF to exist and are investable. We have attempted to maximize the investment universe to all global equity markets (including sector ETFs), select commodity markets that currently have ETFs in the market, Bond Markets (largely $US Sovereign Debt), and FX ETFs (based on US dollar). In all, we have selected 64 asset classes – see Table 4 for select asset classes.
As the longest-serving ETFs only go back to 1994, and we wanted to have at least over 30 years of monthly price data in our test, we have simulated historical results based on index returns using information from MSCI, and the US Federal Reserve FRED database.
We have chosen to not include crypto assets such as Bitcoin and Ether in these back test as we have previously modeled crypto prices and noted that they tend to trade similar to a 5x leveraged NASDAQ index. In future back tests, we may include crypto assets as more data becomes available.
Table 4 – Investment Universe – 1985 to 2021
Asset Allocations BT Momentum – 1985 to 2021
As we mentioned earlier, capital is allocated every month to the top 3 ETFs based on momentum scores in a weighting of 40%/40%/20% to the risk assets.
Below in Table 5, we have noted that the top portfolio allocations over time have been largely allocated to commodities and energy (priced in US dollars), supply of US dollar liquidity, and consistent with a growing global economy over time.
The momentum effect is well known in commodity markets and trend-following strategies are used by commodity trading advisor (CTA) firms, so it is not surprising to see many in the Top 10. Also, countries that benefitted from high economic growth and further development during the period showed higher momentum (i.e. Mexico, China, India, and Russia).
We also note that US REITs have a high allocation over the period, but very little has been allocated to US equities. As we have noted in the past, Real Estate is the largest asset class in the world, and US Real Estate through increasing collateral values and increasing credit creation/higher liquidity is particularly important to the “Wealth Effect” and driving consumption in the US, which helps support the global growth cycle through further consumption. Over each period, the BT Momentum Strategy provides returns at least as good as US equity market returns.
Table 5: BT Momentum Strategy – Average Asset Allocations Over Time
We note that BT Momentum provides some risk diversification to US equity portfolios based on low diversification over the measurement period (below 0.50 for most of the period based on a 3-year rolling correlation) based on Table 6.
Table 6: Rolling Correlation of BT Momentum vs US Equity Markets
The BT Wave Runner Strategy builds upon the BT Momentum strategy by adding a Risk Composite Indicator based on Fundamental data and the BT Market Risk Sentiment Indicator as a risk control to reduce the annual volatility, as the indicator identifies periods of economic and liquidity expansion.
The Market Risk Sentiment indicator is the same one introduced in our first post which helps out monitor the global growth cycle daily and has been highly correlated with the OECD Composite Leading Indicator on a monthly basis.
The idea of this portfolio strategy is simple, to avoid investing in risk assets in volatile periods that tend to be more susceptible to drawdowns (i.e. investor risk appetite tends to change quickly and frequently, which tends to create volatility in momentum portfolios), invest when the trend of liquidity in markets and industrial production/general economic outlook (as measured by the OECD Composite Leading Indicator) is better than the 3-year moving average trend. Or in other words, the trend is your friend.
In periods of more volatile markets, the portfolio is invested in a Safety portfolio based on the 13612W momentum filter of the safety investment universe.
In Tables 6 and 7, we show the results of the simulated portfolio starting with $100 in 1985 (with no future contributions), which has multiplied to $265,000 by end of 2021 based on compound annual returns of almost 25% per year, far outperforming the Wilshire 5000 by 2x and outperformed the Wilshire 50% of the time on a monthly basis. The largest drawdown is about 50% of equity markets as well and offers similar drawdown protection as a 50% risk-asset/50% safety asset portfolio.
The overall correlation of monthly results of the BT Wave Runner portfolio to US equity markets is low (0.20) over the period, thus providing some diversification to standard long-only more heavily weighted equity portfolios. These results are impressive as volatility is roughly that of US equity markets. The BT Wave Runner portfolio strategy offers about 50% of return/volatility of the BT Momentum Portfolio. It offers 42 times the cumulative value of a long-only equity market portfolio by sidestepping large drawdowns and riding the combined waves of momentum and liquidity.
Table 6 – Summary Results – BT Wave Runner Portfolio Strategy vs Wiltshire 5000 – 1985 to 2021 (monthly results)
Table 7 – Summary Results – BT Wave Runner Portfolio Strategy vs Wiltshire 5000 – 1985 to 2021 (monthly results)
BT Wave Runner Decision Rules:
In Table 8, the flow chart reviews the decision rules in the Wave Runner model.
If the Risk Composite Indicator is above trend, we expect that global investor risk appetite should be above trend based on the 13612W momentum filter. As a result, the portfolio is invested in the top 3 asset classes as measured by 13612W. If Risk Composite Indicator is below trend, the portfolio is invested in a safe portfolio allocated to 6 assets that tend to be very safe in periods of extreme market volatility (flight to quality to reserve assets).
Table 8: Decision Rules BT Wave Runner Strategy
The Safety Portfolio:
The safety portfolio is based on the idea that the US dollar and US Treasuries are the world’s reserve assets underpinning the world’s financial system. In our previous post, we have discussed the dominance of the US dollar, US Treasuries, and Gold held by Central Banks reserves as the US dollar holds significant weight in the Financial System. There tends to be a flight to quality (US dollar reserve assets and Gold) when markets are volatile.
As a result, we have restricted our safety allocation to largely US dollar reserve assets. When the Risk Composite is below trend, the portfolio is invested in the top 3 assets based on the 13612W momentum filter based on a weighting of 40% for 1st and 2nd and 20% for 3rd highest momentum.
iShares 20+ Year Treasury Bond ETF (TLT)
iShares 7-10 Year Treasury Bond ETF (IEF)
iShares 1-3 Year Treasury Bond ETF (SHY)
iShares GNMA Bond ETF – Mortgage-backed Securities (GNMA)
Invesco DB US Dollar Index Bullish Fund (UUP)
SPDR Gold Shares (GLD or PHYS)
4. Risk Composite Indicator
The Risk composite indicator is a Z-Score measure based on the following measures below. The weighting of each component of the composite is based on the inverse of the volatility of the Z-Scores for each component.
52% of the time the portfolio is in the safety portfolio (see Table 9 for historical Risk Composite Indicator) and 48% of the time in the BT Momentum Strategy (Risk-on). We should note that we have not fitted this indicator via regression to equity markets to optimize the weighting between the various indicators (this could significantly improve the backtest metrics).
The credit cycle refers to the self-reinforcing interactions between perceptions of value and risk, risk-taking, and financing constraints. Typically, rapid increases in credit drive up property and asset prices, which in turn increase collateral values and thus the amount of credit the private sector can obtain until, at some point, risk appetite reduces due to change in conditions where the debt can no longer be serviced or bankers are no longer willing to supply credit (i.e. increasing unemployment/bankruptcies, pandemics which reduces the labor supply, natural disasters, interest rates are raised beyond the neutral rate of interest, war/tensions, etc.).
Each time a bank creates a loan, a corresponding deposit is created through the banking system, which adds to the money supply. Money is used to purchase goods and services and accumulate and save for a property. As the money supply grows, cash is devalued against assets (financial assets, real estate, commodities, art, etc.), causing nominal prices to rise.
Famed investor Stanley Druckenmiller has said before: “Earnings don’t move the overall market; it’s the Federal Reserve Board… focus on the central banks, and focus on the movement of liquidity… most people in the market are looking for earnings and conventional measures. It’s liquidity that moves markets”.
We can see this in action in Table 10 as BT Global Liquidity Index leads S&P 500 growth by about 12 months. We use information from National Statistical Authorities OECD, IMF, Bank of International Settlements, and US Federal Reserve to calculate the BT Global Liquidity Index.
Table 10: Global Liquidity vs S&P 500 EPS Growth – 1993 to 2022
Financial liquidity explicitly drives investors’ risk appetite and asset allocation. Rising collateral values then positively feedback to underpin new liquidity/credit creation. We have seen that more liquidity has reduced the risk premium on risk assets, as well as cutting defaults, allowing investors to invest in riskier investments/longer duration assets such as technology stocks that may not turn a profit until many years in the future. Higher investment in technology also improves economic productivity, which offsets older demographics that plague most countries globally. We can see below in Table 11, that Global Liquidity, advanced 6-months tends to lead NASDAQ returns (Z-Scores) (a proxy for returns on technology investment).
Table 11: BT Global Liquidity Index vs NASDAQ Returns – 2000 to 2022
We have used a similar methodology that Cross-Border Capital uses to determine Global Liquidity as defined in Michael Howell’s book Capital Wars – “The Rise of Global Liquidity”.
Howell defines Global Liquidity, “as a source of funding that measures gross flows of credit and international capital feeding through the world’s banking system and collateral-based wholesale funding markets. It determines the balance sheet capacity of all credit providers and the private sector’s access to cash through savings and credit”.
Private Sector Liquidity: Includes credit flows from the Banking sector, and Shadow Banking sector (consisting of entities such as asset-backed commercial paper (ABCP) conduits, credit hedge funds, finance companies, government-sponsored enterprises (GSEs), money market mutual funds (MMMFs), securities lenders, insurance/pension and structured investment vehicles (SIVs))
Central Bank Liquidity: Foreign and Gold Reserves and balance sheet allocation to Quantitative Easing programs.
Cross Border Funding: Foreign investors and lenders through cross-border flows. These flows have historically provided a preview of the pending economic crisis and tend to be marginal capital allocated which drives markets.
BT Global Liquidity Index includes flows from the following countries: China, United States, Europe, UK, Japan, Canada, Australia, South Korea, Russia, India, Brazil Mexico, South Africa, Switzerland, and Singapore. Table 12 shows US Liquidity by sector.
Table 12: US Liquidity by Sector
2) Is the OECD Composite Leading Indicator helpful in forecasting the real economy?
The OECD system of composite leading indicators (CLI), first developed in the 1980s, is designed to give early signals of turning points in economic activity.
The CLIs aim to anticipate fluctuations in economic activity over the next six to nine months based on a range of forward-looking indicators such as order books, confidence indicators, building permits, long-term interest rates, new car registrations, etc., as well as a monthly index of industrial production (IIP) as a proxy measure for economic activity. OECD CLIs aim to predict turning points in this business cycle estimate (signal a turning point in the business cycle in 6-9 months).
The CLI is timely and published every month (a lag of about 45 days after month-end) and is more frequently updated than GDP which is usually updated every quarter with a 2-month lag. High-frequency monthly production data such as Plastic production and Electricity consumption appear significant in China and Mexico (countries that rely more on production for economic growth on a relative basis). The OECD CLI is a significant input in our country’s Machine Learning models which we have discussed in prior posts.
The OECD CLI is used within the BT Wave Runner portfolio strategy to aid in assessing the growth/inflation (business) cycle and has been able to identify turning points in advance so that investors may reduce risk exposure in anticipation of drawdowns/market volatility in risk assets.
In Table 13, we observe that GDP growth is strongly correlated with OECD CLI. Based on a Granger causality test, the OECD CLI leads the real GDP growth by about 2-quarters (F=3.7247, statistically significant at 5% level).
We believe the OECD CLI would be useful in measuring the real activity in the economy and is complementary to the BT Global Liquidity Index as we believe the flows of liquidity via the ‘Wealth Effect’ through the financial cycle drive real economic growth.
Table 13: OECD Real GDP growth vs OECD CLI
3. Why Do U.S. Housing Starts Matter?
Housing/Real Estate — and all of the ancillary spending associated with the purchase of a home, including renovation and remodeling costs and utilities — is a huge part of the global economy.
Real Estate is the largest asset class globally. Every recession since 1960 has been preceded by a double-digit decline in housing starts. It can take several months for home builders to construct a new property. And homebuilders are reluctant to break ground on new projects if they fear the economy may slump later in the year.
In our previous post, we have covered the importance of US Real Estate and how it contributes to consumption in the US which drives U.S. GDP growth, and further drives the wealth of the Top 10% within the country. Continuing global growth depends on the consumption of the American consumer and the continuance of the Wealth Effect.
Table 14 – U.S. Housing Starts – Good Recession Indicator?
B. BT Market Sentiment Indicators (50% of the Risk Composite Index):
In our first post, we discussed a daily risk indicator that we have used in our Wave Runner portfolio. To manage and monitor our risk on a more frequent basis, we have attempted to create a customized index that may be tracked daily that aligns well every month with the OECD CLI which tracks the business cycle.
This custom index which we have called the BT Market Risk Indicator includes the following measures:
High Beta (AUD/USD)-to Low Beta (JPY/USD) Currency Pairing
U.S. Discretionary Consumer Spending-to-Consumer Staples Ratio*
U.S. High Yield Corporate Credit to Intermediate Gov’t Bond Ratio
U.S. TIPS Bonds to Intermediate Gov’t Bond Ratio*
* Not included in current 1985 to 2021 backtest given data limitations.
The OECD CLI is a significant indicator based on our research to track going forward, however, there is a lag of about 45 days to report results for a given month. This makes our approach susceptible to quick market drawdowns, such as the one we experienced in February/March 2020. However, looking back during that time the OECD CLI was already in negative territory and would have indicated an extremely cautious risk position in our investment portfolio.
In Table 15, we show that the BT Market Risk Sentiment indicator and OECD CLI tend to move in the same direction over time. We have discussed in our prior posts, the importance of the Copper-to-Gold Ratio and how commodity currencies (Australia dollar, Canadian dollar) tend to follow a cyclical upswing, and generally, during a crisis, there is a flight to safety (U.S. Treasury bonds, gold, and the Japanese Yen). We have also discussed how credit spreads tend to widen in the late-cycle period as market interest rates start to rise higher than the neutral rate of interest, reducing investor risk appetite.
Table 15 – BT Market Risk Sentiment – A Timely Proxy for OECD CLI?
Asset Allocations – BT Wave Runner
The Wave Runner portfolio shows a similar allocation to BT Momentum, however, was able to side steps large drawdowns, and reduce the annual volatility by about 50% (see Table 16).
Table 16 – BT Wave Runner Average Allocation over time (Risk Assets Only)
The Wave Runner Portfolio is in the Safety Portfolio for 229 months out of 443 months (52% of the time). This has significantly reduced the annual volatility, but also lowered the return as well. The Safety Portfolio (when in Risk-off) provides strong returns with limited volatility and drawdown, providing an annual return of about 7% as noted in Table 17.
Capital is allocated to the Safety portfolio based on a similar momentum scoring system (13612W) with about 20% allocated to each Intermediate Treasury, Long-term Treasuries, and Gold (Table 18).
Table 18 – BT Wave Runner Average Allocation (Safety Portfolio)
Though we use US equities as a benchmark, we note that based on the holdings throughout BT Wave Runner (50% risk assets and 50% safety assets) based on the movement of the BT Risk Composite Indicator, the more appropriate benchmark should be measured on similar allocation (50% risk assets and 50% safety), which the BT Wave Runner provides a significant improvement over as cumulative value throughout 1985 to 2021 is 121 times.
In Table 19, we note similar max drawdowns were exhibited by both Wave Runner and Appropriate Benchmark with static allocations at around 25% of capital (both portfolios provide similar improvements relative to risk asset drawdowns).
Table 19 – BT Wave Runner vs Risk Appropriate Benchmark
The overall returns of the Wave Runner portfolio are also significantly non-correlated with US equity markets (see Table 20), more so than the BT Momentum portfolio, given the low-to-negative correlation of the Safety Portfolio to equity markets.
Table 20 – Rolling Correlations – BT Wave Runner vs US Equities
The combination of fundamental and market risk sentiment data as risk control, incorporated with momentum has improved the risk-adjusted returns of the portfolio by riding the liquidity and momentum waves. Who said riding waves isn’t fun?
We have witnessed something we haven’t seen since 1945 in Europe – a world superpower (Russia) invading a weaker country (Ukraine) on its borders to takeover, integrate, and control the state – essentially with the intent of redrawing its borders. From the year 1400 to 2021, there have been roughly 3,708 conflicts within Europe. Each major war since 1600 has lasted about 8 years.
Since the conclusion of WW2 in 1945, Europe has been relatively peaceful, as conflicts continued to be rare events and the forming of the European Union has improved international relations, along with the MAD principle – Mutual Assured Destruction, conflict with a nuclear superpower.
Markets and geopolitics are Complex Adaptive Systems (CAS). CAS is a dynamic and nonlinear network that emerges in the interactions of many entities (elements, components, or agents) that influence and react to one another.
The outcomes of global geopolitics are very difficult to predict, given the many participants and considerations, which makes investing in a changing environment given the amount of uncertainty. The result of the Russia/Ukraine conflict could be Cold War 2.0 or further escalation into World War III or another option not considered.
We have reviewed Russia/Ukraine’s key import and export markets, focusing on food and energy markets. We provide a framework to help investors across the business cycle whether in War or Peace, based on our review of the last 125 years of data across multiple asset classes.
In this post, we will review the current state in the following sections:
Overview of the Conflict – Russia/Ukraine
War and Peace – De-Globalization vs Globalization
War and Peace – Energy Independence and Economic Security
Inflation Expectations and Recession – Stagflation?
Asset Class Capital Returns in War and Peace – A Deep Dive across 125 years
War and Pandemics have been inflationary/stagflationary in general. War and pandemics have been a constant in human history. We have been in a relatively peaceful period since the end of WW2.
The last 20 years may have been an anomaly as peace fostered through diplomacy and trade openness (globalization) has enriched the world and created deflationary forces through higher labor supply from China and former Soviet countries as the first Cold War ended.
Over the past 5 years, Cold War 2.0 has emerged with a very different ideology of how to allocate resources and how rewards may be shared with the East (China/Russia adopting autocratic capitalism) and the West (democratic capitalism). With de-globalization, there may be significant inflationary impacts as the supply chain for sovereign security is being re-shored and separated including energy and food.
Over the past 5 years, we are seeing a multipolar looking to be de-globalize and reorient the world order which is expected to have significant impacts on resource markets over the foreseeable future (energy security/low carbon usage, food/agriculture, technology/cybersecurity, defense budgets, and resiliency of the supply chain by reshoring, autocracy vs democracy, and new monetary order). We review the impact of the current conflict on energy markets and the impact on market-implied expectations for growth, inflation, and interest rates.
Even if there is a negotiated settlement in Russia/Ukraine conflict, we do not anticipate the sanctions to be removed quickly or the food supply chain to get back up and running to be able to meet potential food demand. We believe that the economy may continue to see a stagflation/recessionary economy as costs for a basic living (food, energy, and rent/housing) are expected to continue to rise as a result of the Russia/Ukraine conflict.
We focus on energy markets in this post. We note that the US and Canada have significant oil and gas reserves which may be used to expand production that could be used to replace Europe’s structural shortage for current energy needs, as it looks to transition to a low-carbon future. Further diplomacy and collaboration on a wider energy policy and effective transition plan to a low-carbon energy policy with allies may enhance the energy independence of the West.
By understanding the business cycle and its various seasons (deflation, inflation, growth, and stagflation) within the context of War and Peace we attempt to provide any clues of what may come next, and may help investors allocate capital across the economic cycle by maximizing risk/return tradeoffs.
1. Overview of the Conflict – Russia/Ukraine
War occurs when there are miscalculations. We saw a number of these miscalculations over the past 2 years which enabled Putin to invade Ukraine:
Underestimating Rivals and International Response:
Vladimir Putin (Russia’s President) underestimated Ukraine’s Leader Volodymyr Zelensky and the Ukrainian people’s willingness to defend their country and their way of life.
Putin’s view of the West was in shambles, both politically and culturally, with weak and inexperienced leaders.
For the last 5-10 years the West has focused on “Culture Wars” with increasing polarization at both extremes of populism (left and right), seeing nationalism and liberalism as opposite ends of the spectrum. However, nationalism and liberalism meet together through political freedom, which has allowed the world to unite and object to Putin’s adventurism.
The migration crisis that results from the war from Ukrainian citizens fleeing may increase immigration in the West, which has historically stoked far-right ideologies against immigration in the West. The destruction of Ukrainian cities could be Putin’s attempt to create further cultural divides within democratic countries in the West via immigration.
Putin has taken Europe’s dependence on Russia’s Oil and Gas supply and believed that sanctions may not be levied (or similar to those levied in 2014 when Crimea was annexed) if he invaded Ukraine.
Europe is also focusing on renewables for energy, but the grid is not yet equipped for intermittent sources like wind and solar to fill the gap. The international media and citizens have condemned the carnage of the war and the targeting of civilians by Russia.
As a result, these miscalculations unified the 30 North Atlantic Treaty Organization (NATO) members like never before, solidified Ukrainian national resolve, debilitated the Russian economy, and turned that country (or at least, Putin) into a pariah for years.
Crossing Putin’s Red Line: On Nov. 10, 2021, the US and Ukraine signed a Charter on Strategic Partnership, which asserted the support for Ukraine’s right to pursue membership in the North Atlantic Treaty Organization (NATO). Putin cannot afford to allow life to a neighboring state which has even a smidgen of democratic development. The Russian people might get dangerous ideas and overthrow their leader. Also, by including Ukraine in NATO, Russia would be largely landlocked and bordered by NATO – see Table 1. Putin has been clear for many years that if NATO continued eastward expansion would likely be met with serious resistance by Russia, even with military action. The Russian response is similar to that of the US when USSR sought to deploy missiles in neighboring Cuba in 1962.
Enabling Putin – US and China:
The US missteps: The Biden administration waived sanctions in May 2021 on Russia related to pipeline to Germany (Nord Stream 2) and slowed military aid to Ukraine which included lethal weapons in June 2021. The controversial withdrawal of American troops in Afghanistan seven months ago may have enabled Putin to test American power and resolve.
China’s Missteps: China and Russia on the opening day of the Beijing Winter Olympics declared a “no limits” partnership. In early February, Western intelligence reports indicated that Chinese officials requested that senior Russian officials wait until after the Beijing Olympics had finished before beginning an invasion into Ukraine. At this point, Russia has requested weapons and support from China, but it is unknown at this point whether China will supply and support Russia further. China is also dependent on Russia for energy, food and potentially key resources for clean energy as well. However, China has become Ukraine’s largest trading partner since 2019 and has previously provided Ukraine with nuclear security guarantees upon nuclear invasion or threats of invasion. China also implemented the Western-led sanctions against Russia, despite criticism against sanctions. At the heart of China’s foreign policy strategy lies a conviction that the US is weakened (high debt/internal conflict) from reckless foreign adventures, including goading Putin into the Ukraine conflict.
Table 1 – NATO and Russia’s Eastern Flank
We have seen in the last number of years through strategic competition, the US, Russia, and China have all weaponized their strengths to improve their negotiating power and stop short of going to kinetic war:
US – Financial System/USD Reserves
Russia – Energy – Oil and Gas
China – Supply Chains.
Throughout history, war has been the norm, rather than peace. This latest conflict has the potential has the impact of sending shockwaves throughout the markets and potentially redrawing the world order.
We have discussed the potential for the new monetary order with our post on gold in the multipolar systems with different underpinning ideologies (liberal democratic capitalism – the West and autocratic capitalism – the East), the world potentially moving away from the current US dollar centric financial system. We have now seen how a lot of what we previously discussed is being put into action.
Mark-to-Market Relative Economic Power – A Potential New World Order?
Aging/High Debt Super Power: As we’ve discussed in our previous posts, the US looks very similar to the UK after WWII (high debtor nation, aging superpower) and China appears very similar to the emerging US power after WWII.
Ideal Time to Act as the US is in a Weakened State: Having the inflation at 40-year highs (acts as a regressive tax impacting low-to-middle income earnings disproportionally and makes up a large proportion of the voter base) combined with declining approval rates of the Biden Administration with a stalled domestic agenda and few foreign policy missteps, with a weakened sovereign balance sheet (high debt-to-GDP) coming out of the COVID-19 crisis, may have left an opening for Russia (with limited sovereign debt, a war chest of FX reserves/gold, commodity prices rising, and strong natural resources) to test the resolve of the US while trying to annex Ukraine and other eastern European countries.
We have discussed the possibility of a future multipolar world with China and its allies on one side and the US on the other side based on bilateral central bank liquidity swap agreements. The existence of these agreements tends to be for strong allies and important trade partners.
“No Limits” partnership: China and Russia have been moving away from the US dollar centric financial system, expanding bilateral trade in their own currencies for years and already conduct at least a quarter of cross-border business in rubles and yuan. More contracts in commodities have moved towards pricing in yuan (gold, oil, and natural gas).
Lack of Energy Independence and Leverage: With a quarter of the European Union’s oil imports coming from Russia, along with almost half of its gas, there are concerns that Russia could restrict supplies in retaliation for measures taken against it.
Clock is Ticking, and Now is the Time for Action: With the global transition to a low-carbon future due to climate change along with aging demographics, Russia probably recognizes that there is a limited period to continue to leverage its strong position with Europe’s energy needs relative to clean energy resources, as well as providing a strong military force to expand its current borders to align with its previous imperial borders.
Complacency in Globalization/Culture Wars with Populism on both sides: The West has woken up to the fact that energy security/independence is critical to democracy and freedom. Globalization has moved energy production and carbon emissions away from the West to autocratic leaders (Russia, Saudi Arabia, Iran). We review the Energy market balance between the East and West in a multipolar world, as energy independence potentially provides economic security going forward.
2. War and Peace – De-Globalization vs Globalization
War tends to result in inflationary conditions during and especially in the aftermath of major wars (see Table 2 for major conflicts) due to the following:
Long history of using debt-financed spending to fund increased war-related expenditure (before and during wars) and reconstruction efforts (in the aftermath), driving aggregate demand higher relative to war-damaged supply.
Wars destroy physical capital, driving investment and interest rates higher: Wars are often associated with the widespread destruction of physical capital, a development that increases the investment demand and pushes interest rates higher.
Rationing and disruption of supply chains in food and energy (i.e. restricting supply relative to aggregate demand) tend to cause inflation. Major net exporters of energy or food which are participating in the war may reallocate any surplus from trade to domestic production to support the war effort, making supply scarcer on the world market. Also, destruction of infrastructure, labor shortages, or other transportation modes of moving food and energy to end consumers may cause inflation.
Table 2 – Wars and Pandemics
Peace generally results in more trade/globalization in which surplus food, labor, and energy supply can be exported to countries to trade for better technology or goods. Peace results in more focus on efficiency just-in-time/reduction of inventory rather than a focus on the resiliency of the supply chain.
In peace, defense spending may be reduced or reallocated to education or health care or tackling other priorities such as transitioning from fossil fuels to providing ongoing energy needs. Generally, with surplus production (labor, energy, food, etc) more than demand due to globalization, deflationary trends begin to persist. Global trade openness also significantly promotes peace. Global trade openness has expanded from 1950 to now, see Table 3.
Table 3 – Trade Openness
An increase in global trade openness reduces the probability of military conflict. Globalization promotes peace through two channels:
1) Increased advantage for bilateral trade independence;
2) Integration into the global market
Trade integration results in economic and political gains through a peace dividend. Some countries have resorted to trade restrictions to protect national businesses and jobs. However, protectionism also puts international relations at risk. We have seen some protectionism over the past 5 years which has strained international relations.
There are aggregate gains from trade, but there are also distributional concerns. Even if the trade is not a major driver of income inequalities, government policy, such as unemployment benefits and other safety-net programs, helps redistribute the gains from trade.
Table 4 has reviewed the last 125 years of US inflation data on a 5-year rolling basis – compound annual growth rates (CAGR). We note that coming out of WWI and WWII and Vietnam War inflation has been high (above 5% on a rolling 5-year basis). We note that short-term rates followed inflation up in WWI and Vietnam War situations, though coming out of WWII most countries had heavy debt loads (similar to what we see today), central banks held short-term rates below the inflation rate (financial repression), to reduce debt levels relative to incomes. We have also built a simple index (blue-line) comprised of costs related to food, housing, energy, and wages based on weights in the Consumer Price index (CPI).
Table 4 – 125 Years of Inflation – United States
We note that with globalization/trade openness (peace) increases from the 1980s onwards, CPI (orange-line) has been significantly lower than the Index (blue-line) as lower wages from lower-cost countries have had a significant impact on CPI. In Table 5, we break out main prices related to Basic Living = Food, Housing, Energy, and Wages and note that Food and Energy can be quite volatile coming out of war/pandemic.
Table 5 – 125 Years of Inflation – United States
So How Have Avoided War in Europe for so long? ….Democratic Peace Theory
Dependent on the ideologies of liberalism, such as civil liberties and political freedom, the Democratic Peace Theory which originated from philosopher Immanuel Kant holds that democracies are hesitant to go to war with other democratic countries. Proponents cite several reasons for the tendency of democratic states to maintain peace, including:
The citizens of democracies (the people going to war) usually have some say over legislative decisions to declare war.
In democracies, the voting public holds their elected leaders responsible for human and financial war losses.
When held publicly accountable, government leaders are likely to create diplomatic institutions for resolving international tensions.
Democracies rarely view countries with similar policies and forms of government as hostile.
Usually possessing more wealth than other states, democracies avoid war to preserve their resources.
With the rise of autocracies and shift to populism within democracies with attacks on the West’s democratic institutions that provide checks and balances to political power over the last 5 years, the risk for military conflict expanded. So with this in mind, we aim to cover the sanctions imposed on Russia and why has the West relied on sanctions rather than direct conflict to date.
What are the Sanctions being imposed on Russia?
A sanction is a penalty imposed by one country on another, often to stop it from acting aggressively or breaking international law. Sanctions are often designed to hurt a country’s economy or the finances of individual citizens such as leading politicians or influential citizens. They are among the toughest measures nations can use, short of going to kinetic war.
Without rehashing the entire Ukraine/Russian conflict and related sanctions, the main sanctions/impacts are:
Western leaders have frozen the assets of Russia’s central bank, limiting its ability to access its dollar reserves. This is effectively confiscation of foreign currency reserves, which has much may wider implications going forward.
The US, the EU, Canada, and the UK have also banned people and businesses from dealings with the Russian central bank, its finance ministry, and its wealth fund.
Selected Russian banks will also be removed from the Swift messaging system, which enables the smooth transfer of money across borders. The ban will delay the payments Russia gets for exports of oil and gas.
Western governments have imposed sanctions on some individuals, including a “hit list” of powerful, wealthy businessmen and women close to the Kremlin known as oligarchs.
Russian President Vladimir Putin and his Foreign Minister Sergei Lavrov have also been sanctioned. Their assets in the US, EU, UK, and Canada will be frozen. The US has imposed a travel ban on both of them.
Energy imports (oil, gas, and coal) from Russia were banned from the US, Canada, UK, and Malaysia. This is expected to be a directly hit only a small amount of Russian oil exports, the indirect hit could be much higher because a growing number of traders and buyers will be shunning Russian crude due to “self-sanctioning”/reputational risks.
Many multinational businesses have left Russia
Russia has banned exports of fertilizer, which removes a large part of the market
Ukraine has banned exports of wheat, oats, and other food staples.
Europe sets the 2027 deadline to end reliance on Russian oil and gas. Germany is increasing its defense spending up to 2% of GDP.
Russia is being progressively unplugged from the world economy and disconnected from international forums and activities.
Why focus on Financial Sanctions Rather than Direct Military Force?
The West has focused on Financial Sanctions largely as a result of the ideology in which the West is governed (Democratic Peace Theory), we can see why the path of avoiding direct military conflict with a nuclear superpower (Mutual Assured Destruction – MAD principle) has been chosen and a focus on financial sanctions to weaken Russia’s economy and a proxy war by providing support and weapons to Ukraine.
However, the outcome of choosing this path specific to financial sanctions may weaken the trust and confidence in banking institutions going forward.
A couple of weeks before the Russia/Ukraine conflict, we observed in Canada, the invoking of the Emergencies Act in response to the trucker’s Freedom Convey protest which effectively shut down the capital in Ottawa. The Emergencies Act identified and froze bank accounts of those citizens that donated to the cause. This type of activity may have also weakened the trust and confidence of the banking system as well.
What Can We Expect Going Forward?
In this section, we dig a little further into the broad trade relationships that both Russia (Table 6) and Ukraine (Table 7) depend on to drive their economy forward, to determine if there be further supply shocks across global commodity/goods markets.
Table 6 – Key Exports and Imports – Russia (2020)
We can expect higher energy prices with restrictions of supply due to the loss of Russian oil and gas due to the sanctions. We note that Energy (Oil, Gas, Coal, and Nuclear) accounts for 43.1% of exports from Russia, and 50% of these exports are with the US and its allies. Also, food prices may increase as well as, Russia and Ukraine combine for nearly 33% of the world’s wheat and barley exports. Ukraine also is a major supplier of corn and the global leader in sunflower seed oil, used in food processing.
Table 7 – Key Exports and Imports – Ukraine (2020)
When combining corn, wheat, sunflower seed oil, and fertilizer, Russia and Ukraine combine for 21% of the global market, which is very significant (Table 8).
Palladium is another significant metal mined and exported from Russia, representing almost 40% of the global market. More than 80% of all palladium in the world is mined in South Africa and Russia. Palladium is used in most gasoline-engine catalytic converters. The price of Palladium was up significantly up 33% from the date of the invasion to March 8th, but has subsequently retraced.
The war could reduce food supplies just when prices are at their highest levels since 2011. Typically when food prices increase, social disruption tends to increase (i.e. Arab Spring in 2011). We may yet see more disruption as a result of food shortages. Countries that are major importers of these agriculture commodities include China, India, Egypt, Bangladesh, and Indonesia (some of which are at risk to a social disruption).
We will be watching how this may plan out over the coming months as food shortages are expected to increase food prices, potentially resulting in a further crisis. The energy price (oil price) has a significant impact on food prices, and oil supply is expected to be constrained – see Table 9.
Table 8 – Impact of Combined Russian and Ukrainian Exports as % of Total Market
Table 9 – Food Price Index and WTI Oil Price
Russia relies on the US and its allies for about 44% of its major imports including Cars, Vehicle Parts, Pharmaceuticals, Aircraft, helicopters, and Spacecraft.
This may have short-term consequences depending upon how long the war with Ukraine lasts, but we expect that the financial sanctions will take some time to be removed even after there is a ceasefire or conclusion to the war. There may also be a long-lasting stigma of Russian exports as well, as trade requires political stability and trust.
China may be able to replace the imports from the West, except for high tech, at this point. The West has have targeted semiconductors and other emerging technologies with export controls.
Also, commodity-rich western nations such as Canada, Australia, and Nordic countries over time may be able to replace the exports from Russia through investments in infrastructure and collaborating in the West with like-minded governments (liberal democratic societies) on Energy and Agriculture policy to help secure supply chains, which will be a topic of a future post.
Governments must balance the need for energy security today with a transition to low carbon technologies of the future and this is not a binary decision (i.e. if we build pipelines for natural gas today, we will not invest in climate change, renewables, and electrification of the power grid). The price stability of the economy depends on the price stability of energy from all sources and the encouragement of private investment as well through thoughtful energy policies.
3. War and Peace – Energy Independence and Economic Security
So Could East and West function in a multipolar world?
Energy independence means relying on national or local sources of energy.
Russia exports 4 to 5 million barrels of oil and 8.5 trillion cubic feet of natural gas and Europe is their most important partner and is dependent see Table 10.
Most of oil and gas moves through pipelines as we note in Table 11.
Let’s take a look at the numbers…
Table 10 – Russia’s oil and gas exports
Table 11 – Russian supply lines – Oil and Natural Gas
So the question is with the oil and gas embargos from the West, can Russia redeploy their export supply to China or other Allies. It appears to be complex to move oil and gas physically and could be redeployed through rail but moving through sea or pipeline is going to be a challenge given that Russia currently does not have access to the sea.
The move to Clean Energy in the West has set up structurally higher energy prices (oil and gas) for most of the world due to the lack of investment over the last 10 years has reduced future supply – this is expected to increase inflation going forward as energy is input into almost any produced. Low carbon power generation sources include wind power, solar power, nuclear power, and most hydropower.
Currently, the West has not fully transitioned to low carbon sources, see Table 12 and the world continues to source most energy consumed from fossil fuels (oil, natural gas, and coal) – Table 13.
Table 12 – Share of Low Carbon Electricity
Table 13 – Global Consumption of Energy and Electricity Production
Let’s take a look at Oil and Gas consumption, production, and reserves.
Structural Energy Shortage (Oil and Gas) – West vs East – Global Shortage Inevitable?
We looked at the importance of bilateral swap (BL swap) agreements in the previous posts. These swap agreements stabilize markets when markets become stressed in a fiat currency regime (i.e. debt becomes too much and more than cash flows to repay principal and interest). It also allows us to categorize countries across strategic/trade alliances.
For ease of reference, we have referred to the US and its allies as the West and China and its allies as the East.
Swap lines keep plenty of currency available during times of stress so that countries can continue to trade and secure important raw materials for manufacturing and production. In a fiat currency system, liquidity is necessary to keep financial markets functioning smoothly during crises.
Table 14 – Structural Energy Production Shortage (Oil) in the West
At this point with the West transitioning to a low-carbon future, has a structural deficit (more consumption versus production) of 7.4 million barrels per day despite having 271 trillion barrels in reserve and relies on imports to meet current energy needs choosing to keep domestic production in the ground – see Table 14. Oil reserves are roughly split 50/50 between the West and the East, though this does not include large producers/reserves such as Saudi Arabia, Venezuela, Kuwait, Iran, and Iraq, though all are members of China’s Belt and Road Initiative and appear to be more aligned with China.
In the East, there is a slight surplus of oil, as China’s large deficit of 10.3 million barrels per day could be largely filled by Russia and UAE, and Kazakhstan at current consumption and production. Note we have not included large producers such as Saudi Arabia, Kuwait, Iran, and Iraq – in the table above.
Table 15 – Structural Energy Production Shortage (Natural Gas) in the West, Structural Production Surplus in the East
In the West, there is a structural production shortage of Natural Gas (Table 15) within European Union consuming 32.7 trillion cubic feet per day more than they produce, offset by excess production in Australia, the US, Canada, and Norway. There is surplus production in the East, as the supply deficit in China is more than offset by Russia and Qatar. Natural Gas reserves are heavily weighted towards the East.
Table 16: Significant Oil and Natural Gas Reserves
While oil and gas companies come under pressure to reduce production, the world’s thirst for new supply is only growing. We note that the US and Canada have significant oil and gas reserves which may be used to expand production that could be used to replace Europe’s structural shortage for current energy needs, as it looks to transition to a low-carbon future. Further diplomacy and collaboration on a wider energy policy and effective transition plan to a low-carbon energy policy with allies may enhance the energy independence of the West.
Replacing Russia’s exports of oil and gas with Western allies may be difficult given that current production capacity and infrastructure (pipelines) cannot be easily expanded. Nor are capital providers willing to take the risk, provide investment to expand capacity in an industry with a limited lifespan.
Without a significant uptick in investment, demand for oil and gas will surpass supply in the not-so-distant future.
This disconnect between the political desire for fewer fossil fuels and the global hunger for fossil fuels could drive the price of oil up potentially higher than the current prices.
Hence we are considering how investors may position their portfolios in periods of high inflation or stagflation – Section 5.
In the next section, we look at Nuclear energy as a potential replacement and try to understand the balance of power between East and West.
Nuclear Energy – A Potential Solution to move to a Low-Carbon World?
One may ask the question, to reduce the reliance on natural gas exports from Russia to Europe, without significant investment in pipelines in North America, can we look to another source of energy? Nuclear may be another energy source to review.
As the West transitions to low-carbon future reliance on nuclear energy (which is about 10% of today’s energy consumption) are expected to aid in the transition. Nuclear energy has the highest capacity factor, which has caused the world to take a second look at nuclear to solve the world’s future energy needs.
Uranium is the main fuel for nuclear reactors, and it can be found in many places around the world. To make the fuel, uranium is mined and goes through refining and enrichment before being loaded into a nuclear reactor.
Uranium is found in small amounts in most rocks, and even in seawater. Uranium mines operate in many countries, but more than 85% of uranium is produced in six countries: Kazakhstan, Canada, Australia, Namibia, Niger, and Russia – See Table 17.
Nuclear energy production emits no greenhouse gases, but some constituents voice concern about the potential for accidents and the lack of a permanent disposal repository for nuclear waste, which is radioactive. Germany was getting about 25% of its electricity from nuclear energy until March 2011, when the government passed a law to phase out nuclear power following the Fukushima accident in Japan.
The current Russia/Ukraine war will be a test of nuclear generation given that Ukraine has about 56% of its electricity generated via nuclear and the safety of such power generation in conflict.
Table 17 – Uranium Production
Table 18 – Nuclear Share of Energy by Country and Capacity by Source
Russia has about 20% of the nuclear enrichment capacity and most of the world’s capacity is in the East – Table 19 as well as, the current production capacity of uranium.
Nuclear operators in the West may have to look toward importing enriched uranium from other countries such as France, Japan, and China if there are sanctions put in place on the fuel from Russia.
There are reactors produced in Canada that do not require uranium to be enriched, called CANDU nuclear reactors. 15% of total electricity in Canada is produced via nuclear sources. Also, CANDU reactors are used in China, South Korea, Romania, India, Pakistan, and Argentina.
Table 19 – Uranium Enrichment Capacity
The current conflict should be a wake-up for the West in that energy independence is required for economic and physical security considering both fossil fuel and clean energy sources.
Even if there is a ceasefire in the Ukraine/Russia conflict soon, we believe that the West should transition their trading arrangements to secure, sustainable, predictable trading partners who are also allies and operate according to the democratic peace theory. This includes a comprehensive energy policy including an effective transition plan.
Transitioning the energy grid will take physical upgrades and international coordination and diplomacy. A comprehensive strategy is required to protect and assert the sovereignty of current borders and energy infrastructure.
Resource-rich countries such as Canada, Nordic countries, and Australia should be able to potentially replace Russia’s exports such as fertilizer, crude oil, natural gas, aluminum, wheat, iron, and gold. We hope to take a deeper dive into Canada’s economic potential in a further post.
We are hoping that the recent events may be a cause for reconsiderations of past populist ideologies in the West, which currently favor binary policy choices such as policies to block investment in infrastructure (Keystone XL pipeline) to export oil and gas as a means to fight climate change at all costs. Instead of looking to Canada to replace oil imports, the US is looking to negotiate with autocratic governments such as Saudi Arabia, Iran, and Venezuela to increase production.
Could the West’s De-coupling from Russia impact the West’s transition to Renewable Energy Sources?
As we mentioned in our previous the Magical Power of the Copper/Gold ratio post renewable energy sources require several minerals (see Table 20) that are mined across Latin America, China, Russia, and North America. As we noted that China and its allies have about 40% of global copper reserves, while the US and its allies have about 23% of global reserves. Russia represents about 7% of total copper reserves.
Table 20 – Minerals Used in Clean Energy Technologies
As Russia represents 2% of the global population but 11% of the world’s landmass, it does have an outsized share (>5% of the total market) with a significant share in Lithium, Nickel, Manganese, Graphite, Chromium, Zinc, Rare Earths, and Silicon, which it may export excess resources – see Table 21.
Nickel is a key material in electric vehicle batteries, and the market price had been rising steadily even before the conflict in Ukraine ramped prices on concerns about threats to Russian supplies. Russia accounts for about 10% of global nickel output and traders have been concerned that supplies could be constrained by Western sanctions.
Though, Russia may not have the same influence in the energy market as it does currently in Oil and Gas, but it still, has outsized resources which will be quite valuable in the future – see Table 21. In addition to a common ideology, this may also partly explain China’s “no limits” partnership to source important metals and minerals with Russia for future clean energy production.
Table 21 – Russia’s Influence on Minerals Used in Clean Energy Materials
China has emerged as a major force in global supply chains for critical minerals and clean energy technologies over recent decades. Despite its current reliance on coal to power electricity, the country’s rise to becoming the leader of clean energy supply chains has largely been underpinned by its long-term industrial policies, such as five-year plans for economic development, the Made in China initiative, and the Belt and Road Initiatives – See Table 22.
We also note that the current US import reliance on various transition metals and minerals may reduce its future energy independence. However, we believe allies such as Canada and Australia, along with Latin American sources may provide secure supply chains. In January 2020 Canada and the United States signed a Joint Action Plan on Critical Minerals Collaboration to advance mutual cooperation.
Table 22: New Energy Sources Introduce New Trade Patterns and Geopolitical Concerns
In the short-term, given the world’s reliance on oil and gas for energy today and Russia’s role in the market, we believe this may increase the cost of energy relative to household spending over time. The next section reviews the market’s view of inflation and as a result a potential recession.
4. Impact of the Conflict – Inflation Expectations and a Potential Recession?
Historically every business cycle has ended in recession as inflation peaks. Oil price shocks are also strongly correlated with these inflation peaks (see Table 23). During previous war periods, energy prices also increased as supply was constrained and supply chains were at risk (physical delivery of oil).
The combination of higher food and energy prices, along with the tightening of monetary conditions are expected to reduce consumer expectations and consumption, resulting in recession.
Table 23 – US Economic Growth vs Inflation
Inflation Expectations – Starting to become Unanchored in Short-term
On Table 24, Inflation has been above trend in 2021 and 2022 due to supply chain and fiscal stimulus as a result of COVID-19, though we have started to note market-implied cyclical expectations have started to become unanchored from the 2% target and are currently at 3.5% as the red-line has moved to the right of the blue-line.
In Table 24 we note that the current quarter (Q1/2022) with inflation of ~8% and unemployment below 4%, is a very rare occurrence.
Based on historical probabilities since 1955, we note that when inflation is above 4% and the unemployment rate is below 4%, over the next 12-24 months has historically resulted in recession 100% of the time.
The amounts do not include the impact on the inflation related to the Russia/Ukraine conflict, which is expected to cause inflation to go even higher. The Cleveland Fed Nowcasting model for Q1/2022 is forecasting an 9% annualized change.
Table 24 – Inflation and Unemployment – Historical Probabilities
In addition to the realization that inflation is not transitory, the conflict in Ukraine/Russia has moved up the expectations as a result of higher energy and food prices. Tightening of monetary policy is not expected to resolve the supply constraints related to energy and food associated with the conflict and supply chain resolutions as a result of COVID-19.
The labor market continued to be very strong, though real wage growth remains negative. The Federal Reserve Bank of San Francisco has recently looked at an alternative metric to measure the economic output gap (RGDP and Unemployment) and has suggested direct measures of the degree of labor market tightness, such as the vacancy-to-unemployment ratio (V/UR), provide superior inflation forecasts for prices and wages (Table 25), which may guide the Federal Reserve in monetary policy decision making.
This is an alternative to the statistical measures of output gaps the inflation-targeting central banking typically relies upon. The V/U ratio represents the number of job vacancies, or demand for labor, relative to the number of unemployed individuals, or supply of labor or marginal cost of labor. As both unemployment and inflation are lagging indicators, raising the Fed Funds rate to a level that reduces the V/UR ratio by increasing unemployment to reduce inflation back to the target of 2% and potential GDP.
Table 25 – Marginal Cost of Labor (V/U Ratio) vs Inflation
In Table 26, we note that the probability of inflation increasing above 3% over the next 5 years implied by markets is about 60% which is much higher than historically observed. This indicates there is a higher probability of inflation tail risk (>3%).
Table 27 – Market-Implied CPI Expectations over next 5 Years and Probability
However, we note in Table 28, that long-term expectations inferred by 5-year inflation expectations, 5 years forward implied by markets in Table 29 have remained largely unchanged, which suggests to us that higher inflation is largely cyclical as expected in the near term due to supply constraints, up to 3.4% over the next 5-years implied by the market. Structural inflation does not appear to be impacted as 5-Year Inflation expectations, 5 years forward expect to be 2.15% (close 2% target).
In Table 30, Market-implied Fed Funds rate 1-year from now is expected 200-225 bps (7 hikes – blue-line) up from 6 hikes at the end of January (orange-line), as it is expected to bring creditability back to prices and expected that as monetary policy tightens, unemployment is expected to increase. However, supply shocks via war/pandemic are not going to be directly solved by tightening monetary policy. Central banks tend to be less hawkish during wartime.
Table 30 – Short-term Interest Rate 1-year from now
The Fed will need to balance price stability versus jobs and provide optionality should the war in Ukraine expand beyond its borders and potentially embroil NATO or potentially the knock-on effects of sanctions in Russia resulting in a significant credit event which represents a major risk. So raising rates on autopilot may not be a viable option.
Growth Expectations – Are we starting to see signs of recession?
Even before considering the impact of Russia/Ukraine on energy and food prices and any moves by the Federal Reserve in the next few months will be into a slowdown of economic activity as a result of the tightening of financial conditions, and higher energy prices.
Over the past 9 months, consumer sentiment has declined by 30% and is the lowest since 2011. Personal finances were expected to worsen in the year ahead by the largest proportion since the surveys started in the mid-1940 pointing out that the high inflation rate is impacting incomes.
Further increases in inflation due to Russia/Ukraine conflict are expected to reduce the misery index potential to the low points we have seen during the Great Financial Crisis and high inflation of the late 1970s – see Table 31.
As we noted in the Wealth and Debt, Two Sides of the Same Coin post, the wealth effect and consumption are a significant part of the US GDP (about 70%) and consumer confidence is important to continue to drive this consumption forward. Also as higher energy and food costs disproportionally impact low-to-middle income earnings, which make up a greater proportion of the population, lower consumption may lead to lower GDP growth going forward.
The current Real GDP nowcast for Q1/2022 is at 1.3%, which is below-trend growth of 2%, and combined with inflation nowcast of 8-9%, would suggest that we are in the “Stagflation” phase of the business cycle. We review this concept and how asset classes may behave across the different economic phases of the business cycle further in section 5 of this post.
Table 31 – Consumer Sentiment vs Misery Index (Inflation and Unemployment)
We note that higher energy and food prices may also have an impact on corporate earnings and may see an earnings recession in the next 24 months based on historical analysis – Table 32.
Due to the rapid rise of energy prices, higher interest rates, a stronger dollar, higher food prices, and reduced consumer sentiment (represented by the orange line), this is expected to reduce profit margins and profit growth (represented by the blue-line) going forward, which increases the probability of an economic recession.
Table 32 – S&P 500 Earnings YoY vs Index (US dollar, 10-Year Yields, Food, and Oil)
We have also noted yield curve slope has flattened dramatically in the last few months as the 2-year yields have expanded much faster than 10-year yields, with the higher inflation prints which are looking more persistent. Historically flattening/inverting of the yield curve has been a strong predictor of recession conditions (predicted each recession over the past 60 years – see Table 33.
Table 33: Yield Curve Slopes
Given that there have been significant geopolitical moves in the past 3 weeks, we summarize below the main takeaways for investment allocation:
The weaponization of the Financial System and US dollar: Countries with significant commodity exports held in FX reserves may be at-risk if significant military aggression is taken as liabilities/frozen may be confiscated by the US. This may further accelerate the de-dollarization of the financial system. This may make sovereigns hold more of their export surplus in gold. It may make others recalculate any aggressive moves on current sovereign borders. Also, these actions may weaken any trust and confidence in the supporting institution of capitalism (banking and capital markets).
Property rights of a private citizen in the foreign jurisdiction may not apply if significant aggression is taken by a sovereign.
The energy policy of the West must balance fossil fuels and low carbon sources, as the economy modernizes to new forms of energy to help fight climate change.
With globalization, the West has moved the mining of fossil fuel offshore/waged proxy wars, and focused on consumption domestically. In a de-globalized world, energy security may be more of prioritization with local mining from domestic sources and trading with allies such as the European Union, rather than keeping domestic sources in the ground and focusing 100% renewables. A more effective policy may see natural gas and nuclear paired with renewables as a sustainable transition plan, working with like-minded allies that believe in democracy and freedom rather than autocracy.
Food and Energy crises may be upon the globe at the same time due to the Russia/Ukraine war given the importance of both countries to energy and food supply chains. We do not believe historically we have seen a similar situation. In section 5, we review the last 125 years to determine if there is an analogous situation, where we may see high inflation and low growth, also known as Stagflation.
With the economic sanctions, the Russian economy may collapse in the next few months resulting in potential debt defaults which may be worse than collapses in 1918, 1991, and 1998. The second-order impacts of such an event are a large unknown at this time which introduces significant market and economic uncertainty. The conclusion is to remain relatively cautious as an investor during this time.
Over the past 5 years, Cold War 2.0 has emerged with very different ideas of how to allocate resources with the East (China/Russia adopting autocratic capitalism) and the West (democratic capitalism). With de-globalization, there may be significant inflationary impacts as the supply chain for sovereign security is being re-shored and separated including energy and food. We hope that the current Ukraine/Russia conflict may be settled through negotiated settlement soon, though, recognize that this may be the opening act of World War III.
Even if there is a negotiated settlement in Russia/Ukraine conflict, we do not anticipate sanctions to be removed quickly or the food supply chain to get back up and running to be able to meet potential food demand. We believe that the economy may continue to see a stagflation/recessionary economy.
In our next section, we will review capital returns over the past 125 years, as well as the past 40-years on a quarterly basis, to get a better idea of what assets perform well in a stagflationary environment.
5. Asset Class Returns – War and Peace
Given the significance of the conflict to the world economy and related food and energy supply, we have reviewed historical returns by asset class on an annual basis over the past 125 years and the last 40 years on a quarterly basis across 4 economic cycle seasons: 1) Stagflation 2) Growth 3) Inflation 4) Deflation to determine what works as far as portfolio allocation. See Table 34. We looked at how war vs peace may impact these cycles.
We note we are currently in the “Inflation” phase which is defined as above-trend growth and inflation. Though, as oil price shocks have tended to result in recession, we look at “Stagflation” as “Recession” asset class returns.
We reviewed financial assets (large-cap equities, long-term Treasuries, REITs, etc) as well as hard assets/commodities (agriculture, base metals, and precious metals).
In measuring trend Real GDP growth and CPI change we used a common method of measuring potential output is the application of statistical techniques that differentiate between the short-term ups and downs (cycle) and the long-term trend (structural) based on demographics, debt, and technology/productivity changes.
The trend is interpreted as a measure of the economy’s potential output and the cycle as a measure of the output gap relative to this trend. The Hodrick-Prescott (HP) Filter is one popular technique for separating the short from the long term. We have used this technique in estimating the Business Cycle.
Table 34 – Asset Classes and Phases in the Economic Cycle
Table 35 – Economic Growth and Inflation – Actual vs Trend
In Table 35, we review the last 125 years of US economic growth and inflation, we note that the business cycle trend (lasting 10 years) economic growth (Real GDP) of 2.0% and 2.2% Inflation (CPI). These trend factors are used to classify the economic cycle across the following – deflation, stagflation, inflation, and growth. We note that previous wars/pandemics have led to spikes in growth and inflation.
Median annual asset class returns are shown in Table 36 over the past 125 years. Real returns have been positive in Real Estate and Large Cap Broad Equities, and slightly negative across all other asset classes.
During high inflation periods (Inflation and Stagflation), Real Estate, Energy (Oil), Base Metals, and Agriculture commodities tend to outperform other asset classes. Interest rates are significantly higher in a stagflationary environment, which potentially move discount rates higher on large broad equities and result in capital losses on Long-term Treasuries.
Table 36– Asset Class Returns – 1895 to 2021
Review of Previous Wars/Pandemics – Annual Asset Class Returns/Economic Cycles – 1895 to 2021
Let’s take a look at asset class returns during war/pandemic periods in more detail considering the various economic cycles we have defined above. We have added one year after the official end of the war/pandemic to see if any supply shocks drive higher inflation as life gets back to peacetime.
In Table 37, we note that war/pandemic years are more likely to see higher than trend inflation either in Inflation or Stagflation phase, which is consist of supply restriction for key goods in production and supply chains may be attacked as well – pandemic (labor) and war (energy/food/housing), which causes demand to outstrip supply and price levels rise.
Table 37 – Summary of Economic Cycles – 1895 to 2021
Table 38 – World War I and Spanish Flu – 1914 to 1921
In Table 38, we note that the beginning of WWI started at below-trend RGDP and inflation (deflation). You can see war is highly inflationary given supply constraints, moving between stagflation and inflation. Real interest rates were kept negative over the period (inflation greater than rates), keeping the economy at full production.
Over this period, Real Estate and Energy (Oil) have performed well but failed to keep up with the average rate inflation of 8.1%. Large-cap broad equities (S&P 500) and Long-term bonds (TLT proxy) were largely flat over the period, benefitting largely during deflationary periods.
Table 39 – World War II – 1939 to 1946
In Table 39, we note that the beginning of WWII started at above-trend RGDP and below-trend inflation (Growth). You can see war is highly inflationary given supply constraints, averaging 4.2% over the period. Real interest rates were kept negative over the period (inflation greater than rates), keeping the economy at full production to help support the war effort. Real Estate and Agricultural commodities outpace the pace of inflation.
Large-cap broad equities (S&P 500) and long-term bonds (TLT proxy) were negative from a real rate perspective.
Table 40 – Vietnam War 1961-1976
In Table 40, at the beginning of the Vietnam War (1961) started in Deflation (below-trend RGDP and inflation. There is a much more gradual build of inflation over the period, which differs from WWI and WWII spikes in inflation during the war years. Real interest rates were positive over the period.
The oil price shock of 1973-74 was significant, causing inflation to move to double-digit growth on an annualized basis, which was a result of a supply-side shock due to an oil embargo by Arab producers against those countries supporting Israel (in the Yom Kippur War).
During this bout of stagflation, we note that asset returns on real assets (real estate oil, agriculture, base metals, and gold), performed well, despite interest rates rising.
Fed Chairman at the time Arthur Burns argued that the inflation appeared to be the result of a plethora of forces: “the loose financing of the war in Vietnam . . . the devaluations of the dollar in 1971 and 1973, the worldwide economic boom of 1972-73, the crop failures and the resulting surge in world food prices in 1974-75, and the extraordinary increases in oil prices and the sharp deceleration of productivity”
Economists have since come to understand that a central bank can influence the extent to which supply shocks affect inflation, but they face a trade-off.
Higher oil prices, because of the widespread effect they have on commodities throughout the economy, will tend to generate both inflationary pressures and slower growth. In the short run, these forces tend to have an inverse relationship, meaning when one rises, the other falls, and vice versa.
Unfortunately, monetary policy cannot offset the recessionary and inflationary effects of increased oil prices at the same time. If the central bank lowers interest rates to stimulate growth, it risks adding to inflationary pressure; but if it raises enough to choke off the inflationary effect…it may exacerbate the slowdown in economic growth.
The decision to tighten or ease monetary policy ultimately depends on how policymakers balance the risks inherent in pursuing employment and price stability objectives.
History may not repeat, but it certainly rhymes as the fact base appears somewhat consistent when reviewing our current emerging risks due to the Russia/Ukraine conflict as energy and world food prices are expected to increase as supply is expected to be constrained.
However, we do note that there are some differences in the fact pattern as inflation had been building in the economy during the late 1960s/early 1970s as well, and the first Baby Boomers – whose generation was defined by the boom in U.S. births following World War II (largest generation the world experience at that point) began to enter the labor force, potentially drove up consumption and demand for resources during this time. The labor force participation and labor force growth are much lower now than in the 1960/the 1970s.
There is the potential for policy errors from central banks by misreading the situation by continuing to raise rates and maintaining a hawkish stance into a slowing environment, without considering risk management considerations. Also by not recognizing the very clear threat of Russia waging unconventional war via the economy in retaliation for sanctions including cyberattacks on US financial institutions. This may take a dynamic approach by the Federal Reserve.
As well, it may be expected should growth begin to fall and stagflation starts to take hold, that fiscal measures may be taken to offset the higher costs related to basic living expenses – rent, food, and energy which is (largely outside of the control of the Federal Reserve) via direct transfer by the government (which is the tool policymakers introduced during the COVID-19 crisis) to ensure that consumption continues to remain buoyant.
Quarterly Review – Post-Bretton Woods Fiat Currency Regime – 1976 to 2022
As we mentioned in our last post, in 1971 (Type 3 system) the monetary system was delinked from gold and the US dollar and US Treasuries backed by the full faith and credit of the United States has continued to play a central role in the international monetary system during the latter part of the 20th century due to the country’s economic strength and the stability of its political and judicial system.
As we noted fiat money could be created in unlimited quantities through the private banking system to support the real economy or by the government issuing debt and monetizing the debt via quantitative easing, if foreign countries were not willing to buy the debt in periods of crisis, to support the de-levering of the private sector.
As a result, given the nature of unanchored credit-based systems, business cycles are much longer than pre-1971, and credit cycles do not build quite as high.
This impacts asset class returns, specifically, gold as fiat currency can be created to drive the economy forward, and we can that cash has been devalued relative to gold as nominal returns are higher across stagflation and inflation. Thus, we have reviewed quarterly data given the move to the fiat currency (Type 3 system).
Table 41: Summary of Economic Cycles – 1976 to 2022
In Table 41, the proportion of the quarters split by deflation, stagflation, growth, and inflation are very similar to the annual review we provided earlier with growth (higher RGDP than trend, and below-trend inflation) representing 35% of the quarters. However, there has been a lower occurrence of the Deflation phase of about 7% moving from 28% to 21%, as the previous monetary backed by gold had been deflationary at times.
In Table 42, we show based on the phases of economic cycle based the different quarterly returns (sequentially quarterly returns) by asset class, to pick up changes in the economic season reflected in asset class prices.
Table 41: Asset Classes by Quarter – Q2/1978 to Q1/2022 (Quarter-over-Quarter Returns)
Based on historic probabilities, deflation (below-trend growth and inflation) or stagflation (below-trend growth and above-trend inflation) in combination are about 40% probability in a given quarter. Growth (above-trend growth, below-trend inflation) is the most likely at 35% probability in a given quarter.
During stagflation similar to what we have noted earlier asset returns on real assets (real estate/REIT, oil, agriculture, and gold), performed well, despite interest rates rising. This is a similar finding to the annual analysis.
Technology stocks have performed well across deflationary, inflation, and growth environments, though have specifically underperformed during stagflation. Bonds have performed well in deflationary environments due to capital gains as rates fall in these environments.
We do not have a long enough time series to include Bitcoin or Ether, but based on our previous post we believe these assets to act similar to leveraged 5x Technology stocks (QQQ).
Overall Bonds (TLT/IEF) have not protected capital from a real return perspective as real interest rates have been declining and are now deeply negative.
REITs perform well across most environments and potentially the wealth effect we described in our previous post drives these asset returns.
We noted a similar pattern over the past 45 years of quarterly data moving generally moving from Growth to Inflation to Stagflation back to Deflation. This pattern generally takes 4.3 years to play out and since 1976, there have been 11 different cycles – see Table 42.
You will note that generally, each phases lasts about 4 quarters (Deflation, Stagflation, and Inflation) and Growth is about 7 quarters. This table also shows the general stability of returns across asset classes and the importance of portfolio diversification as well for the different economic phases. Being able to anticipate a change in phase, may also help in tilting the portfolio weightings as well. We will go through this topic in a future post.
Table 42: Asset Classes by Phase of the Economic Cycle – Q4/1978 to Q1/2022 (QoQ Returns)
To this point, we have only reviewed average asset class returns, without considering the risk of returns. The volatility of returns and potential for drawdown is always important to consider as well across these various parts of the business cycle.
In Table 43, we have calculated Expected Losses by Asset Class. There is a 1% probability that sequential quarter-over-quarter losses are greater than what is shown in the table. We also get a sense of when the largest drawdowns are in each economic cycle. For example, REITs, Technology, Large Cap equities, Copper, Ag Commodities all have a greater likelihood of large drawdowns during Deflationary parts of the business cycle. Also, the largest drawdowns occur in the second quarter in which the economy is in the “Deflation” phase (recall average Deflationary phase is 4 quarters) and tend to be the setup the next bull market for equity markets.
Higher returns in large-cap/technology equities are expected in the deflationary phase, as higher downside risk is taken on by investors during this phase of the economy and returns are commensurate with the risk taken on. We observe the same theme in the stagflation phase as oil prices have high returns relative to high downside risk as well.
In the “Stagflation” phase, bonds tend to underperform and have the greatest probability of large drawdown. Oil and Gold are expected to have the largest drawdown during the “Growth” phase.
Table 43 – Expected Losses at 99% Confidence Level and Other Measures (Sequential Returns)
In Table 44, we show the expected losses based on annual returns for each asset class by economic cycles, which generally follow the quarterly results in Table 43. Who says markets are disconnected from economic conditions!
Table 44 – Expected Losses at 99% Confidence Level – Annual Returns – 1895 to 2021
Identifying Bottoms in Equity Bear Markets
Now that we have reviewed the Business Cycle Phases and Risk and Return Characteristics of each asset class, we look at another metric in Table 45 that helps identify equity market bottoms. Finding market bottoms is important in the Deflationary phase of the economic cycle, but can been used in any phase.
The CBOE Volatility Index, or VIX, is a real-time market index representing the market’s expectations for volatility over the coming 30 days. VIX is interpreted as an indicator of the level of investor confidence or fear in the market, and therefore the level of investment risk, but it is commonly known as the “uncertainty index.” VVIX represents the volatility of volatility in the sense that it measures the expected volatility of the 30-day forward price of VIX
Historically, the VVIX/VIX ratio tends to be lower during periods of extreme volatility and higher during periods of relative complacency. Market participants also use the ever-changing relationship between VVIX and VIX to monitor the market’s prevailing risk dynamic—through a metric known as the “VVIX/VIX ratio.”
We have calculated the Z-Score (normalized by average and standard deviation) and note that at a Z-Score below -1 (green circles highlight the levels), this provides investors a bottom in which market pessimism is very high and the valuation of the market is cheap. These opportunities tend to be when the economy is in the “Deflationary” or “Stagflation” phases and when the Fed Reserve enacted accommodative monetary policy otherwise known as the “Fed Put”.
The Fed put is a belief by financial market participants that the Federal Reserve will step in to boost the markets if the price of the markets falls to a certain level. However, we believe the Fed Put is much lower than -1 Z-Score this time, given the acceleration of inflation and we will wait to see how this plays out with the Fed’s plan to hike rates over the coming 12-months.
Table 45 – Identifying Equity Market Bottoms – VVIX-to-VIX ratio
How to Position Capital Today…..
We have reviewed the current Russia/Ukraine conflict, its impact across markets including sanctions, and provided a framework to help investors across the business cycle whether in War or Peace, based on our review of the last 125 years of data across multiple asset classes.
In a future post, we hope to demonstrate how we may be able to get a forward-looking view of the transitions of the phases of the economic cycle in real-time based intermarket analysis, so that investors may be able to position their portfolios accordingly.
We noted that war/pandemic years are more likely to see higher than trend inflation either in Inflation or Stagflation phases, as a result of supply restriction for key goods in production, and supply chains may be attacked as well.
The combination of kinetic and financial war as a result of Russia/Ukraine, is expected to reduce the global output of energy and food (effectively an attack on food/energy supply chain). We have observed, that expected growth based on the Atlanta Fed GDP Nowcast is below-trend growth of 2%, and combined with the Cleveland Fed inflation Nowcast of 8-9%, would suggest that we are moving from the “Inflation” phase to the “Stagflation” phase of the business cycle.
Based on our review of the past 125 years of data, during high inflation periods (Inflation and Stagflation), Real Estate/REITs, Energy (Oil/Natural Gas/Uranium), Base Metals (Copper/Aluminum), and Agriculture commodities (Wheat, Soybean, Corn, Sugar, Coffee, Cocoa, Swine, Beef, and Cotton) tend to outperform other asset classes.
Historically, interest rates are significantly higher in a stagflationary environment relative to other phase, which potentially move discount rates higher on large broad equities and result in capital losses on Long-term Treasuries, which are asset classes that underperform during this phase.
Though given the current level of debt on Western sovereign balance sheets, interest rates may not be raised to a level that will tame inflation, also supply shocks via a war/pandemic are not going to be directly solved by significantly tightening monetary policy. We may see Western sovereigns let inflation run hot, which potential hurt citizens, lenders and reduce confidence in the government’s ability to manage the economy.
As well, it may be expected should growth begin to fall and stagflation starts to take hold, that fiscal measures may be taken to offset the higher costs related to basic living expenses – rent, food, and energy which is (largely outside of the control of the Federal Reserve) via direct transfer by the government (which is the tool policymakers introduced during the COVID-19 crisis) to ensure that consumption continues to remain buoyant. This type of action would lead us back to the “Inflation” phase. We will continue to monitor.
We appreciate any questions or feedback you have or other research topics you may suggest.
In our last post we covered the background of the wealth effect and how housing and stocks to drive economic growth. In this post we will cover the following topic:
How does Debt impact the Wealth Effect?
Why is understanding Credit Cycles and Business Cycles are Important ?
A Deeper Dive – The Wealth Effect and Economic Growth in the US – 1975 to 2021
Why are Interest Rates and Debt-Service-Ratio Important to Watch for an Economy reliant on the Wealth Effect/Debt Growth?
1) How does Debt impact the Wealth Effect and Economic Growth?
What is the Long-term Credit Cycle?
The credit cycle refers to the self-reinforcing interactions between perceptions of value and risk, risk-taking, and financing constraints. Typically, rapid increases in credit drive up property and asset prices, which in turn increase collateral values and thus the amount of credit the private sector can obtain until, at some point, risk appetite reduces due to change in conditions where the debt can no longer be serviced or bankers are no longer willing to supply credit (i.e. increasing unemployment/bankruptcies, pandemics which reduces the labor supply, natural disasters, interest rates are raised beyond the neutral rate of interest, war/tensions, etc.).
Historically, this mutually reinforcing interaction between financing constraints and perceptions of value and risks has tended to cause serious macroeconomic dislocations. Risk assets (Corporate Equity/Stock and Real Estate) prices tend to follow the credit cycle on the way up and down.
The Bank of International Settlement (BIS) has done a fair amount of work in this area and can be described by the following:
Financial cycle/Credit Cycle peaks tend to coincide with banking crises or considerable financial stress. During expansions, the self-reinforcing interaction between financing constraints, asset prices, and risk-taking can overstretch balance sheets relative to income/cash flows, making them more fragile and sowing the seeds of the subsequent financial contraction.
The Credit Cycle can be much longer than the Business Cycle. Business cycles as traditionally measured have tended to last up to eight years, and financial cycles or Credit Cycles around 30–60 years since the early 1980s. The difference in length means that a financial cycle can span more than one business cycle. As a result, while the financial cycle peaks can usher in recessions, not all recessions are preceded by such peaks….we cover this later on.
There is a strong link between the pace of debt accumulation and subsequent debt service, which in turn has a large negative effect on growth.
Credit cycles describe the changing availability—and pricing—of credit. When the economy is strong or improving, the willingness of lenders to extend credit, and on favorable terms, is high.
When the economy is weak or weakening, lenders pull back, or “tighten” credit, by making it less available and more expensive, contributing to asset values and further economic weakness and higher defaults.
So How Does One Measure The Credit Cycle?
A common method of measuring potential output is the application of statistical techniques that differentiate between the short-term ups and downs (cycle) and the long-term trend (structural) based on demographics, debt, and technology/productivity changes.
The trend is interpreted as a measure of the economy’s potential output and the cycle as a measure of the output gap relative to this trend. The Hodrick-Prescott (HP) Filter is one popular technique for separating the short from the long term. We have used this technique in estimating Long-term Credit Cycle and Business Cycle. We used a smoothing factor of 400,000 for quarterly data in determining the trend which is consistent with BIS research.
We used an HP Filter to de-trend the data (separate the trend from the cycle) using between 1-8 years for the business cycle using Real GDP (light blue line) and 30-60 years for the long-term Private Credit Cycle (orange line). This is a similar method used by central banks/economists.
The Private Credit Cycle (Table 1) is measured by taking:
Real Private Credit Growth (Household and Corporates) – Table 2;
Real Residential Real Estate Prices – Table 3;
Real Estate Price-to-Rent – Table 4;
Real Estate Price-to-Income – Table 5; and
Private Credit-to-GDP ratio – Table 6.
However, there is a boom-bust cycle in which the boom part of the cycle is characterized by the higher risk appetite of households and corporates which increase and lever up their balance sheets through debt to grow their returns on capital. At some point, risk appetite is reduced (as interest rates rise) as debt service overwhelms underlying cash flows. In response, the fiscal authorities run large deficits (light-grey-line) during the bust part of the cycle, to allow the private economy (household and corporates) to de-lever and bring debts back in line with cash flows (see Table 1)
Table 1 – Long-term Credit Cycles – 1890 to 2021 – United States
Table 2 – Real Private Credit Growth (Household and Corporates)
Table 3 – US Real Residential Real Estate Prices
Table 4 – US Real Estate Price-to-Rent
Table 5 – US Real Estate Price-to-Income
Table 6 – US Private Credit-to-GDP ratio
What is a Business Cycle?
Business cycles are a type of fluctuation in aggregate economic activity in market-oriented economies. Business cycles are recurrent expansions and recessions in an economic activity affecting broad segments of the economy. The business cycle goes through four major phases: expansion, peak, contraction, and trough.
The Central Bank helps to manage the cycle with monetary policy, while fiscal authorities use fiscal policy. A nation’s central bank influences the business cycle by targeting inflation and unemployment with targeted rates and other unconventional policies such as quantitative easing. It uses tools designed to change interest rates, lending, and borrowing by businesses, banks, and consumers, which in turn drives real GDP higher over time.
The central bank lowers its target interest rates to encourage borrowing in attempts to end a contraction or trough to increase declining real GDP and deflation. This is called expansionary monetary policy because they are attempting to push the business cycle back into the expansionary phase.
To keep the economy from growing too quickly (real GDP and inflation) and take on too much debt, the central bank raises its target interest rates to discourage borrowing and spending. This is called “contractionary monetary policy,” because the bank is trying to contract economic output to keep expansion under control.
Expansionary fiscal policy aggregate demand by increasing government spending or lowering taxes—can be used to close a negative output gap. We would have witnessed fiscal stimulus during the latest pandemic which was used to close a negative output gap (real GDP below the potential GDP), reduce the unemployment rate, and increase inflation.
The goal of fiscal and monetary policy is to keep the economy growing at a sustainable rate while creating enough jobs for everyone who wants one and is slow enough not to increase inflation.
The output gap is an economic measure of the difference between the actual output of an economy and its potential output. Potential output is the maximum amount of goods and services an economy can turn out when it is most efficient—that is, at full capacity
The output gap measures the degree of inflation pressure in the economy and is an important link between the real side of the economy—which produces goods and services—and inflation. All else equal, if the output gap is positive over time so that actual output is greater than potential output, prices will begin to rise in response to demand pressure in key markets. Similarly, if actual output falls below potential output over time, prices will begin to fall to reflect weak demand. See table 7 –which shows the US Output gap over time.
Table 7 – Real GDP ($B) versus Potential Real GDP (CBO) ($B) and Output Gap (RGDP)
The unemployment gap is a concept closely related to the output gap. Both are central to the conduct of monetary and fiscal policies. The nonaccelerating inflation rate of unemployment (NAIRU) is the unemployment rate consistent with a constant rate of inflation
Deviations of the unemployment rate from the NAIRU are associated with deviations of output from its potential level. Theoretically, if policymakers get the actual unemployment rate to equal the NAIRU, the economy will produce at its maximum level of output without straining resources—in other words, there will be no output gap and no inflation pressure. Table 8 shows the Output gap from an unemployment perspective. The Federal Reserve’s dual mandate is “stable prices” and “maximum employment,” referring to inflation and unemployment. It sounds complicated but means ensuring that the prices you pay for goods and services remain relatively stable over time and that everyone who wants a job in the U.S. economy can find one. Typically, when the output gap (RGDP and unemployment) becomes positive, this means the economy is performing above potential output and higher inflation above the target of 2%, which is what we are seeing in early Q1/22. To reduce demand and slow the pace of economic growth, interest rates are expected to be raised.
Table 8 – Unemployment Rate vs NAIRU and Output Gap (Unemployment Rate)
The Federal Reserve Bank of San Francisco has recently looked at an alternative metric to measure the economic output gap (RGDP and Unemployment) and has suggested direct measures of the degree of labor market tightness, such as the vacancy-to-unemployment ratio (V/UR), provide superior inflation forecasts for prices and wages (Table 9).
This is an alternative to the statistical measures of output gaps the inflation-targeting central banking typically relies upon. The V/UR ratio represents the number of job vacancies, or demand for labor, relative to the number of unemployed individuals, or supply of labor or marginal cost of labor. As both unemployment and inflation are lagging indicators, raising the Fed Funds rate to a level that reduces the V/UR ratio by increasing unemployment to reduce inflation back to the target of 2% and potential GDP.
Table 9 – Job-Vacancy vs Unemployment Level
In Table 10, we show the various business cycles documented by Economic Cycle Research Institute across various countries since 1948. We discuss in the next section how central banks use various tools to influence monetary policy and influence the business cycle.
Table 10 – Historical Business Cycles across Several Countries – 1948 to 2020 (ECRI)
How do Central Banks Influence the Business Cycle with Monetary Policy?
Central banks vary the short-term interest rate (overnight lending between banks known as interbank lending) based on the business cycle as measured by the output gap whether it is positive or negative. In influencing the business cycle, Central Banks use three primary tools:
Setting the current overnight interbank rate
2. Forward guidance to influence the expected future interest rates
3. Quantitative Easing (QE) or Quantitative Tightening (QT) – targeted purchases or sale of long-maturity bonds and other long-duration assets on the central bank balance sheet. This is how central banks influence the term premium. Longer-term bond yields, tend to be set by market demand and supply of bonds based on long-term growth and inflation expectations. However, as central banks buy a larger proportion of domestic sovereign bond markets via QE, interest rates will no longer be solely set by the markets. Currently, the US Fed Reserve owns about 30% of the sovereign bond market.
Long-term Maturity Bond Yield = Expected Central Bank Interbank Interest Rate + Term Premium
By varying the current interest rate, the expected path of future interest rates, and term premium, central banks influence long-maturity bond yields. Long-maturity yields, influence a variety of borrowing rates (the most popular mortgage rate in the US the 30-year term) and asset valuations1 across the economy, which impact aggregate spending, employment, and inflation via the wealth effect as we discussed in Part 1.
In Table 11, we reviewed the impact of long-term inflation and growth expectations (structural) versus short-term interest rate expectation (cyclical) by performing a regression on various points on the yield curve (2-year, 5-year, 10-year) and expectations (inflation and real GDP over the next 10 years) and 3-mth T-bill rates (one-year forward). You will note that 10-year yields are determined by long-term inflation and growth expectations, whereas shorter-term yields such as 2-year rates are much more influenced by short-term expected interest rates (cyclical) based on the current monetary policy stance.
Table 11 – Yields (10-Year, 5-Year, 2-Year) vs. Long-term 3mth rate, RGDP and Inflation Expectations (10-year)
Longer maturity bonds depend on long-term inflation and growth expectations
The term premium is the extra return required to hold to maturity a long-maturity bond versus rolling over short-maturity debt (e.g.3-month T-bills). The term premium is largely driven by economic factors beyond the current monetary policy stance, particularly over long-term horizons such as long-term expectations (inflation and real GDP growth), as well as savings/investment by households, and demand/supply of sovereign debt.
Term Premium = Inflation Uncertainty + Safe-Haven Savings + Net Demand/Supply of Sovereign Debt
QE influences bond yields by reducing term premium and QT increases term premium. The term premium is generally counter-cyclical – both inflation uncertainty and investor risk aversion tend to be higher in recessions than in booms – a flare-up in safe-haven demand can further suppress term premium and bond yields over the near term.
Structural impacts are impacted by demographics which future impact will growth rates.
Other structural impacts include savings vs. investment, and saving glut/inequality. Structural elements impacts both the natural rate of interest and term premium.
The declining US working-age population (Table 12) will affect long-term yields/term premiums in 2 ways: 1) lower growth potential will lower neutral rate, and 2) higher demand for safe assets (bond vs equities) given that retirees tend to reduce their equity market risk. The shift in supply/demand balance will weigh on risk-reward for holding long-term. On the other hand, the number of retired households is expected to rise and begin to consume rather than save, thereby contributing to a lower saving rate and may lead to an increase in the natural rate of interest.
Table 12 – Term Premium vs Growth in Working-age Population
How Could We Anticipate Central Bank Monetary Policy?
Simple Monetary Policy Rule – The Taylor Rule – Setting the Overnight Interbank Rate
The Taylor Rule (TR), which is a simple formula that Economist John Taylor devised to guide policymakers. It calculates what the federal funds rate should be, as a function of the output gap and current inflation.
Central Bank Interbank Interest Rate = Natural Rate of Interest + Current Inflation Rate + 0.5 (Inflation Rate – Inflation Rate Target) + 0.5 (Output Gap) where:
Inflation Target = 2%
Inflation = Core Personal Consumption Expenditures (Excluding Food and Energy)
Output Gap = the percent deviation of real GDP from a Potential GDP (based on Congressional Budget Office Potential Output and BT model based on 10-year business cycle) (discussed above)
Natural Interest Rate = long-run equilibrium interest rate or neutral real rate, is the rate that would keep the economy operating at full employment and stable inflation (based on Laubach-Williams r-star model).
The TR captures the intuition the central bank should set a higher interest rate when inflation exceeds its target and a lower interest rate when inflation is below its target. The TR prescribes a real interest rate above r-star when the inflation gap or output gap is positive, and a real interest rate below r-star when the inflation gap or output gap is negative. There are several variations of the TR depending on the inputs and assumptions.
In Table 13, we have provided our application of the estimate for the Fed Funds Rates based on the Congressional Budget Office estimate of potential RGDP. You can see that the Fed Funds Rate has followed the Taylor Rule pretty closely over time and there have been times where the Federal Reserve has lagged slightly. We note the inflation gap in 2021-2022 is significant given the fiscal stimulus related to COVID-19, and supply chain issues, though the output gap has only started to close in the last quarter and there are signs the economy is starting to slow into H2/2022 from the demand side and the supply side, we are seeing easing in the ports and shipping rates (Baltic Dry Index).
However, the Russia/Ukraine conflict (including various sanctions) and China’s no-COVID policy could potentially be a further source of higher than target inflation going forward in the supply chain. We saw a similar deviation from the Taylor rule that last time we saw high inflation in the late 1970/the early 1980s and Fed had to overcorrect. However, we have much higher debt-to-GDP now relative to this time.
Looking back at the 1940s to 1950s (see Table 14), coming out of WW2 the debt level was similar to current levels coming out of the COVID-19 pandemic, and you will note that real interest rates were negative (inflation greater than interest rates). This financial repression allowed to get rid of the high levels of debt through keeping interest rate levels deliberately below the rate of inflation. We believe this will be a similar strategy used this time around as well.
Table 13 – Taylor Rule Fed Funds Rate vs. Fed Funds Rate – Q1/1961 to Q4/2021
Table 14 – Real Interest Rates vs Debt Levels
At high levels of debt, financial repression (setting rates below of rate of inflation) has been used to reduce leverage (Debt-to-GDP)
We’ll discuss how interest rates influence debt-service, asset valuations, and credit/business cycle further in section 4.
2) Why is understanding Credit Cycles and Business Cycles are Important in an unanchored Fiat Currency System – A Review of the US – 1975 to 2021?
So why don’t we just track the business cycle?
As we mentioned in our last post, in 1971 (Type 3 system) the monetary system was delinked from gold and the US dollar and US Treasuries backed by the full faith and credit of the United States has continued to play a central role in the international monetary system during the latter part of the 20th century due to the country’s economic strength and the stability of its political and judicial system.
As we noted fiat money could be created in unlimited quantities through the private banking system to support the real economy or by the government issuing debt and monetizing the debt via quantitative easing, if foreign countries were not willing to buy the debt in periods of crisis, to support the de-levering of the private sector.
As a result, given the nature of unanchored credit-based systems, business cycles are much longer than pre-1971, and credit cycles do not build quite as high (see Table 15). Generally, the Credit Cycle peaks at about 7-10% above trend like it recently have in 1979, 1988, and 2007. By the end of 2021, US Credit Cycle was about 10% above trend.
In all cases, the Credit Cycles tend to reverse course as the Federal Reserve raises the Fed Funds rate. These peaks are also associated with equity market peaks in the S&P500 before large drawdowns within the next 12 months or so. Troughs have existed in 1993 and 2012.
Peaks in the credit cycle are associated with the Federal Reserve’s lagging the Taylor Rule Federal Funds Rate by a significant deviation of 2-3% for a period that allowed an asset price bubble to form in stocks and real estate.
Table 15 – US Private Credit Cycle vs U.S. Real GDP – 1890 to 2021
So you may ask what has changed since 1971 that has supported increasing the length in the Business Cycle and Credit Cycles. Well, several things:
Financial markets were liberalized starting in the 1980s. Without sufficient prudential safeguards, this change is likely to have allowed greater scope for the self-reinforcing interactions at the heart of the credit cycle to play out.
Inflation-focused monetary regimes became the norm in reaction to high inflation of the late 1970-early 1980s. This led central banks to downplay the role of monetary and credit aggregates in their frameworks.
The combination of growth in the working-age population (see Table 16), further participation from women, supply squeeze for oil, and liberalization of credit in 1970-the 1980s were potentially drivers for the high inflation during 1970-1980s.
Central banks had little reason to tighten monetary policy if inflation remained low due to globalization (lower labor and goods costs), even as financial imbalances built up (including high house prices to income).
This focus on inflation targeting may have also reduced real wage growth and may have increased asset prices and the wealth effect, further exacerbating wealth inequality. Also, tax policy across many countries focused on investing in assets relative to labor.
Push towards globalization: The entry of China and former communist countries into the world economy, alongside the international integration of product markets, and technological advances, boosted the global supply of labor reduced local labor negotiating power. Given the capitalist nature of many of the Western economies, moving production to low-cost jurisdictions maximizes corporate profits, though hollowing out manufacturing sectors. This generated returns to shareholders and households that owned stocks.
Demographic changes: Working-age population as % of the population (see Table 16) in the West first increased until about 1990s and declined thereafter, causing economies to rely more on capital/wealth effects and investments in technology to improve productivity to drive Real GDP growth forward rather than labor. Structural factors such as regulation and taxation responded to support this movement away from labor towards capital. Slowing labor supply has also reduced natural rates over time…more on this later.
Further banking regulation (Basel Committee on Banking Supervision) was introduced to differentiate risk-based lending (lower credit risk weights generally for loans collateralized by residential real estate) and support the system in market stresses (government debt treated as a highly liquid asset) to maintain the existing system of lending and borrowing.
Table 16 – Working Age Population (Age 15 to 65) as % of Total Population
Coupled together financial booms could build up further and a turn in the credit cycle (i.e. increasing unemployment or bankruptcy, pandemic, etc), rather than rising inflation and the consequent monetary tightening, would trigger an economic downturn. This also appeared to have a lengthening effect in the business cycle. So many market participants focus on central bank tightening and inflation cycles on determining the length of the business cycle, without considering the credit cycle and impact of the interest rate changes on debt-service ratios.
3) A Deeper Dive – The Wealth Effect and Economic Growth in the US – 1975 to 2021
To understand the wealth effect and the credit cycle, we need to take a deeper dive into the US wealth distribution.
At a high level, the US relies on a higher proportion of household spending at almost 70% of GDP and is much more unequal from the perspective of both wealth and income, as the Top 10% wealth has 70% of the country’s wealth and more wealth is in financial assets relative to real estate (see Table 17) than other countries we’ve reviewed.
As we noted in Part 1 Table 2, the ratio of Mean Net Wealth to Median Net Wealth was 7.0, which far surpassed the average of countries reviewed and income inequality was the highest with a 0.40 Gini coefficient.
Table 17 – US Household Net Worth and Wealth Distribution – 1987 to 2021
Through this inequality, the average wealth of the US has been maximized which is consistent with the American system of capitalism to maximize profits and capital gains of financial assets supported by capital markets. Lowering the cost of capital (through lower natural interest rates), has lowered the barrier for risk-taking within innovation and technology in the hopes of achieving outsized financial net wealth. The US continues to lead in technology and innovation as measured by patents and this is supported by underlying capital markets. A symbiotic link has existed between wealth creation and job creation. When businesses prospered, employment expanded and communities thrived.
The bottom 50% of net wealth in the US derives a larger proportion of their wealth in real estate assets (see Table 18) and changes have been volatile over time given the higher proportion of leverage used in Real Estate. The Top 10% of net wealth derives its wealth from stocks and has generally exhibited less volatility over the last 40 years (see Table 18).
Table 18 – Top 1% and Bottom 50% Net worth Percentiles vs Equity and Real Estate Prices
The wealth effect via real estate is shown in Tables 19 and 20, as we note that Real Home Price Index (HPI) returns are strongly negatively correlated with 30-year mortgage rates (-0.74) and 30-year treasury bonds (-0.83) (which is the most common mortgage term for housing the US). Since 1990-early 2000, we note as the labor share of GDP declined in the US due to outsourcing, Real Estate has appeared to be more important to drive consumption forward. Mortgage Rates have followed 30-year Treasury rates and much of the decline in real interest rates have been the general decline of natural interest rates….more on this later.
In Table 20, we note that as Real HPI is strongly positively correlated with Consumption as % of GDP (0.84), so it thought as Real Estate prices increase net wealth increases and consumption increases (consuming domestic services and a combination of domestic/imported goods). We note that home price increases appear largely on the demand side (lower rates for mortgages and wealth effect) rather than constraining supply (as population growth outstrips housing supply) as the population-to-dwelling ratio has remained relatively steady (slightly declining over the last 20 years) over the past 20 years we have data on (Table 21) and housing supply follows the business cycle largely. This dynamic is important to understand as many countries in the West rely on immigration for economic growth.
Over the last 30 years, inequality has increased and there has been a shift of 10% in total net worth from the bottom 90% to the top 10% (see Table 17). Gains in net worth during 2020 and 2021 were the largest for the least wealthy (bottom 50% of wealth distribution).
Table 19 – US Real Housing Prices vs 30-Year Real Mortgage Rates
Table 20 – US Real Housing Prices, Real Disposable Income (DPI), and Consumption as % of GDP
Table 21 – US Price-to-Income/Rent vs dwelling supply metrics
Looking at the Credit Cycle and Business Cycle together (Table 22), we note that during the late 1970s and 1980s, the credit cycle and business cycle tended to follow one another closely as labor/working-age population was a larger contributor to GDP growth over this period (see Table 23) as consumption and income shares for a large proportion of the country was better aligned. Since the year 2000, the Top 10% of Wealth has grown from 60% to 70% and more private consumption appears to be driven by this small cohort as the labor share has declined over the same period. This has led to a higher debt burden placed on the bottom 50% for housing and consumption.
Table 22 – US Long-term Credit Cycle and Business Cycle – Q1/1976 to Q4/2021
Table 23 – Labor Compensation as % of GDP – 1976 to 2021
We note that income, consumption, and wealth were more evenly distributed during this time. Over the past 40 years, the US has increased wealth and income disparities and both wealth and income have flown to the top of the distribution, resulting in a higher debt burden placed on the bottom 50% for housing and consumption.
Throughout the 1990s-2000s, globalization was the focus through outsourcing the manufacturing base to countries with ample labor supply (China and other emerging markets) at a lower cost-reducing labor compensation as % of GDP since 2000 and increasing profits for those that owed financial assets (stocks). In a healthy economy, companies continually are born, fail, expand, and contract, while new jobs are created and others are destroyed. Over the last 30 years, competition has been reduced and industries have been consolidated with large firms taking a larger share of the overall profit pool.
This lead to potentially relying on the top 10% wealth for a greater proportion of spending and investing. This reliance on a small proportion of the population for consumption and indebtedness of the bottom 90% for housing and consumer consumption potentially weakens Real GDP trend growth going forward. The top 20% of income distribution consumes 40% of the US total annual resources and can save almost ~20% of their income. This is particularly concerning, rather than financing investment in productive capacity, the savings have been associated with dissaving/debt accumulation. The U.S. economy requires political commitment and resolve to protect the robust competition that spurs productivity growth and improves living standards, even when well-resourced interests resist.We discuss this more later on…
You may notice that the recession 2000-2001 did not have a typical peak in the credit cycle, but something else was going on here. Looking at table 24, US equity markets reached a peak (tech bubble) during the time (2000-2001) and consumption patterns (grey line) appear to follow the equity deviations from 2001 and onward. It is very difficult to bifurcate the impact of the stock market relative to real estate impact on consumption though.
Table 24– US Long-term Credit Cycle/Equity Markets and Private Demand (Consumption & Investment)
In Table 24, we also note that the deviation in 2007-2008 of credit cycle/real estate coincides with the Great Financial Crisis (GFC). High levels of mortgage debt can therefore aggravate downturns and increase economic volatility. Indeed, downward pressure on house prices can adversely affect economic activity via wealth effects that lower consumption and via bank balance sheets and reduced new lending. During the US subprime crisis, non-recourse arrangements allowed borrowers with negative home equity, especially those that had bought to let or resell rather than occupy, to strategically walk away from their mortgage debt.
To get the economy (real GDP) going post GFC, the Federal Reserve lowered interest rates and flooded the markets with liquidity, and bought financial assets (bonds) in an attempt to lower long-term interest rates causing financial assets (stocks) to rise, and increase the confidence/risk appetite of investors and consumers. This was helpful for those Americans rich enough to own stocks and continued to increase the wealth gap within the country. The borrowed money was essentially interest-free, so investors and corporate borrowers took advantage of the situation and drove profits and stock prices up. The money did not trickle down to the bottom of the wealth or income distribution, so wealth and income gaps continued to grow.
Overall the American system appears to maximize average net wealth per citizen rather than median wealth, and favors financial assets (stocks) relative to housing which indirectly impacts economic output – this is consistent with a capitalist economy.
The US has a capitalist market economy that utilizes both markets and government regulation and intervention to distribute resources, where the vast majority of value-producing assets are under private ownership and are operated to maximize profits and capital gains from financial assets (stocks).
A recent paper (February 2021) by Mian, Staub, and Sufi called the “Saving Glut of the Rich” highlighted the large rise in savings of Americans in the Top 1% of income or wealth distribution over the past 40 years, rather than financing investment in productive capacity, the savings have been associated with dissaving/debt accumulation by the non-rich in the distribution via housing debt and consumer credit and the government.
The research finds that lenders indirectly used the top 1% saving deposits to finance borrowing by the bottom 90%, enabling the rich to benefits from debt repayments.
The analysis also suggests that the top 1% of households in the US may have as much influence as emerging market economies in fueling the debt of the bottom 90% of the wealth distribution.
Income distribution has been consistent over time, with high-income (top 20%) earning about 50% of the income (Table 25), and income outstripping consumption (Table 26), has enabled substantial savings by high-income earners over the last 30 years. The gains and savings experienced by the wealthiest households mainly reflect higher rates of return of capital and dividends (stocks), which have largely outpaced returns on real estate and wages over the past 40 years.
A proportion of these savings appears to have been placed in the banking system through time/savings deposits funding growth in household debt/real estate prices, as well as stocks.
Table 25 – Growth in Household Income by Quintile
Income across all cohorts grew ~4% annually and distribution remained similar
High-income/wealthy households have accumulated substantial financial assets that are direct claims on the US government and household debt (mortgage and consumer credit). We have summarized this comparison on Table 27 – Banking Net Asset by Wealth Distribution, and note that the Top 10% of the Wealth Distribution effectively benefits from the debt repayments, and the share of the claims via financial assets (time/savings and checking deposits) by the Top 10 grew by ~6% since 1989, which is in-line with high-income earners (top 20%) being able to save an additional 6% of income (see Table 17).
Table 26– Income, Consumption, and Savings by Quintile
Savings increased for high-income earners dramatically since 1989, at the expense of lower consumption/lower Real GDP, as aggregate consumption-to-income declined from 98% to 82% in 2020. The increase in savings has found its way into the banking system (see Table 27) and financial assets such as stocks.
A large rise in inequality generates a ‘savings glut of the rich’ which has pushed the economy into a debt trap characterized by 1) Low-Interest Rates, 2) High Debt Levels, and 3) Output below Potential (Real GDP below Potential Real GDP).
These elements have been observed in the current system and we will discuss the implications in the next section Natural Rate of interest which discusses the decline of interest rates over the last 40 years. This decline in rates has improve asset valuations as well.
These elements have also been discussed in the context of the rise of political populism and polarization which has particularly intensified coming out of the Great Financial Crisis given the large wealth and income gaps. Typically when wealth and income gaps become large as they are now, these have historically devolved into civil wars a Ray Dalio has warned given the amount of political polarization and differing views on how resources in the economy may be allocated (labor vs. capital).
Coming out of the COVID-19 crisis, many countries have begun to question the strategy of globalization and supply chain risk/security in the face of rising international political tensions and the potential for conflict. It appears that re-weighting the US capital allocation more towards labor relative to capital and investment in domestic productive capacity (such as computer chip manufacturing and rebuilding domestic infrastructure) may help reduce the wealth gaps over time and potentially raise the natural interest rates and reduce supply chain risks, however, this may be at the determinant to the Top 1% of wealth holders. The increase in inequality has reduced potential Real GDP over time as well (Table 28) and the neutral rate of interest….
Table 27 – Banking System Net Asset by Wealth Distribution
Table 28 – Real GDP vs Total (Public and Private) Debt Trends
Note: Real GDP Trend-based 10-year business cycle through the application of a statistical filter. Real GDP Potential from US Congressional Budget Office (CBO) estimates retrieved from FRED Federal Reserve.
4) Why are Interest Rates and Debt-Service-Ratio Important to Watch for an Economy reliant on the Wealth Effect and Debt to drive economic growth?
a) What is the Neutral or Natural Rate of Interest?
The natural rate of interest, also called the long-run equilibrium interest rate or neutral real rate, is the rate that would keep the economy operating at full employment and stable inflation and is said to be operating at trend Real GDP growth over a five to ten year period.
It is a function of the economy’s underlying characteristics (labor, capital, productivity) and is not “set” by the Federal Reserve, but in some sense can be thought of as the Fed’s target interest rate when the economy is at full strength.
Understanding the real natural rate (or r-star) matters because it affects how the Fed steers interest rates, which impacts asset values (important to countries that rely on the wealth effect to drive growth).
The Fed may temporarily set the benchmark Fed funds rate, the rate at which banks borrow from each other overnight, below or above the natural interest rate to stimulate or cool the economy, but will ultimately rely on its estimates of the natural rate to decide the direction rates should go and the level rates should reach. Since households and businesses make investment and savings decisions now based on what they think interest rates will be in the future, the Fed’s views on the natural rate have immediate importance.
The Natural Interest Rate or R-star is thought to be unobservable. Economic theory implies that the natural rate of interest varies over time and depends on the trend growth rate of output – higher trend Real GDP growth would increase the natural rate of interest. The level and variability of the estimated natural rate of interest depend on variables used to approximate the underlying inflation expectations. Below are a few simplifying formulas for the above concepts:
Output Gap (Real GDP) = Potential Real GDP/Trend GDP less Actual Real GDP
Output Gap (Unemployment Rate) = Actual Unemployment Rate less Non-accelerating inflation rate of unemployment (NAIRU)
Nominal Neutral Rate = Real Neutral Interest Rate (R-star) + Expected Inflation (over the long-term)
The Laubach-Williams (LW) (2003) model uses data on real GDP, inflation, and the federal funds rate to extract trends in U.S. economic growth and other factors influencing the natural rate of interest. You will note since 1960 rates have declined. As Williams’ notes, there are numerous potential influences on the natural rate of interest, including, but not limited to, fiscal policy, technological change, and demographics. As of November 2020, LW natural rates of interest are no longer being published.
In Table 28, we show that when the real Fed Funds rate (orange line) moves above, the natural interest rate (blue-line), the business cycle reduces actual GDP below potential GDP to reduce inflation back to target and increase unemployment. You can see that Corporate Debt Service Ratios tend to peak (along with widening credit spreads) during these tightening cycles when the Real Fed Funds Rate is above the Natural Rates. As we are about to embark on a rate tightening cycle, we hope to establish early warning indicators. We’ll look at this in the next section.
The natural rate of interest has been on the decline since the 1960s. Many reasons for the bond bull market/declining rates have been cited including:
Demographics (decline in working-age population/labor supply) – we covered this earlier,
Global savings glut (as creditor countries such as China, Germany, and Japan have invested excess US dollars in government bonds lowering the rate of interest),
Wealth inequality/credit creation increasing by higher savings by higher-income households, and
Reduced productivity over time (average from 1947-2018 has been 2.1%, but since 2005 productivity has been 1.3% and declining to 0.8% from 2010 to 2018)
Table 28 – Real Interest Rates vs Business Cycle vs Debt Service Ratio – 1977 to 2020
However, reduction in real interest rates has been something going on for the last 800 years as documented by the Bank of England’s working paper “Eight centuries of global real interest rates, R-G, and the ‘suprasecular’ decline, 1311–2018” which covered 80% of advanced countries.
Capital accumulation/debt accumulation trends have been proposed for what has caused the decline over time rather than demographics, indifference to the central bank or fiscal policies, commodity-backed regimes (i.e. gold), and other factors. The paper also suggests that expansionary monetary and fiscal policy responses designed to raise real interest rates from current levels may have at best a cyclical effect (See Table 29).
Table 29 – Real Interest Rates over the last 800 Years (1311 to 2018)
As Mian, Staub, and Sufi note, the demand for US dollar-denominated safe assets comes almost as much from the top1% in the US as demand from the rest of the world (China, Japan, and Germany).
One area that has not been examined in great detail has been the impact of Top 1% savings and debt accumulation by the bottom 90% since the 1980s and higher total debt-to-GDP ratio (public and private). We note in Chart 28 the Real GDP Trend growth has declined by 100 bps from 1976 to 2021 (or 75% of 1976 trend growth) as Total Debt-to-GDP has expanded by 2x.
b) Why is the terminal rate lower each rate cycle?
Recessions in 2000, 2008, 2020 are all associated with Fed rate hiking cycles and generally rise 2-3% above trend to reduce the level of economic activity to bring Real GDP back in line with Potential GDP/Trend over roughly 2 years (the last cycle is the exception), which pushed debt-service ratios (DSR) up significantly from trend (see Table 30) as households and corporates fail to anticipate higher rates and may be over-levered. Interest rates are cut and government debt increases (fiscal impulse) and is used to de-lever the private sector (see Table 31).
As a result of these actions, Total Debt-to-GDP has increased over time and debt is only reduced when it is repaid or written off. We propose that the terminal rate is lower each rate cycle given the level of debt which keeps increasing to drive growth forward. You can see that Fed Fund Rate Trend has a strong negative correlation with the Total Debt-to-GDP ratio. The flip side of the higher household and government debt is the saving glut mentioned earlier. As more debt is taken on growth becomes weaker.
Table 31 – Private Credit Cycle vs. Fiscal Impulse
Table 32 – Fed Funds Rate vs Total Debt-to-GDP
You can see that the Fed Funds rate has followed CPI deviation from the trend which is consistent with inflation-focused monetary regimes (see Table 33).
The historic hiking cycles generally are 2 years. Current market pricing (Overnight Index Swap curve) has the Fed Funds rates reaching terminal by end of 2023 and following roughly the same historical pattern of a 1.5 to 2% hike from a recent trend of 0.5% Fed Funds Rate, potentially suggesting a very short tightening cycle this time around.
Table 33 – Consumer Price Index Inflation (CPI) and Fed Funds Rates
While higher-income households tend to have higher debt loads, debt payments as a proportion of household disposable income are larger for lower-income households. We tend to watch changes in debt-service ratios and changes in interest rates rather than output gaps (Real GDP vs Potential Real GDP or unemployment gaps) alone as a determining factor of the changes between business cycle – growth and recession, given the level of debt within the economy held by a large proportion of the population in most countries and we don’t have separate debt-service ratios for different points of the wealth distribution.
We have noticed a recurring pattern reviewing runs to 2000, 2008, and 2020 recessions in the US. When short-term real rates rise above long-term real rates, private debt-service (households and corporates) levels tend to increase above trend reducing the growth rate of the economy as employers begin to lay off employees to maintain profit margins, and in a high debt economy, interest rates need to be lowered or fiscal stimulus provided directly to indebted customers as we saw during COVID-19 in 2020.
In Tables 34 to 36, we have attempted to estimate the business cycle to better understand the interaction of interest rates, Long-term Private Credit Cycle, Fiscal Impulse, GDP, and Private Debt Service Ratio.
Estimated Real GDP (blue-line) and unemployment gaps (orange-line) using a statistical filter assuming a 10-year business cycle trend.
We have compared the Real Fed Funds Rate and the Real Long-term Equilibrium rate when tends to follow the output gaps.
Real Fed Funds Rate (grey-line): We have used the 3-month Treasury yield as a proxy for the Fed Funds Rate less Long-term Average of Survey of Professional Forecasters from the Philadelphia Fed (over next 5-10 years), to help us map out the future path of the Federal Reserve. Expectations are usually in the market before the central bank moves.
Long-run Equilibrium Rate: We have used the 10-year Treasury rate using a statistical filter assuming a 10-year business cycle less Long-term Average Inflation from the Survey of Professional Forecasters from the Philadelphia Fed (over next 5-10 years). Given the long-term nature, we believe this would pick up underlying trend factors of labor, capital, and productivity.
We’ve discussed the Credit Cycle (yellow-line) and Fiscal Impulse (light-blue) and note that oscillation between the two impulses, appears to have an impact on the output gaps, as the government comes in with their balance sheet (typically during the recession) when the private sector decrease.
Private Debt-service Ratio Deviation from Trend (green-line): Bank of International Settlements (BIS) data which began disclosing private DSRs beginning in 1999 which can be compared across countries. We have applied using a statistical filter assuming a 10-year business cycle to determine the trend, extracted the cycle (or deviation from trend). It takes 2-3 quarters of the Real Fed Funds Rate above the Long-run Equilibrium rate to reduce growth (output gap below zero) and results in a recession.
Corporate Credit Spreads (BBB) Deviation from Trend (purple-line): We have applied using a statistical filter assuming a 10-year business cycle to determine the trend, extracted the cycle (or deviation from trend). We note that the purple-line generally follows the Private Debt-service Ratio Cycle green-line as the market anticipates increases in credit risk.
Table 34 – US Output Gap, Credit Cycle/Fiscal Impulse and Real Rates
Table 35 – US Private Debt Service Ratio vs Interest Rates
When short-term real rates rise above long-term real rates, private debt-service (households and corporates) levels tend to increase above trend, which tends to lead to recession. Therefore, the slope of the yield curve (yield curve inversion) tends to be quite predictive by leading about 12-months.
We intend to measure other select G20 nations to determine if similar patterns and cycles emerge over time so that we could use these as early warning indicators to reduce risk assets before recessions.
Join us for our next series of posts on the Canadian economy and how housing contributes to growth.
Appreciate any questions or feedback you have or other research topics you may suggest.
1. What is the Wealth Effect? – Background and Overview
The “wealth effect” is the notion that when households become richer as a result of a rise in asset values, such as corporate stock prices or home values, they spend more and stimulate the broader economy. The economic phenomenon of the wealth effect owes its power to consumer psychology and Central Banks’ have become customer psychologists, impacting customer perceptions for consumption and investing via rate expectations and quantitative easing/tightening and attempting to recalibrate interest rates in the economy relative to the real natural rate of interest, to bring the economy back in-line with potential output growth as measured by Real Gross Domestic Product (GDP) potential also known as the business cycle which tends to last about 8-10 years. They may use macro-prudential policy and regulation to manage longer-term risks associated with the credit cycle/housing price trends tend to last over a 20-40 year period. We will attempt to extract the cycles from the trends for both the business and credit cycles so that we are better prepared for what may come at us next.
In a series of posts over the next couple of weeks we plan to cover:
The ‘Wealth Effect’ and Debt – Two Sides of the Same Coin – Part 1
Wealth Effect – Background and Overview
How Credit Contributes to Economic Growth
What are the Main Drivers of House Prices in Advanced Economies?
The ‘Wealth Effect’ and Debt – Two Sides of the Same Coin – Part 2
How does Debt impact the Wealth Effect?
Why is understanding Credit Cycles and Business Cycles are Important – A Review of the US – 1975 to 2021?
Why are Interest Rates and Debt-Service-Ratio Important to Watch for an Economy reliant on the Wealth Effect/Debt Growth?
We will cover the US market in this series of posts. In the next posts, we plan to review the select G20 countries’ wealth effects’ impacts specific to housing/stock ownership on their economies.
The increased value of housing and stock prices on paper makes consumers feel more confident in the economy’s prospects. Feeling more confident, they spend more and become more willing to buy goods and services by taking out more credit increasing their risk appetite.
Our financial system supports asset values by increasing credit creation over time. Each time a bank creates a loan, a corresponding deposit is created through the banking system, which adds to the money supply. Money is used to purchase goods and services and accumulate and save for a property. As the money supply grows, cash is devalued against assets (financial assets, real estate, commodities, art, etc.), causing nominal prices to rise.
As a result, households feel like they have more wealth and believe as they are richer they may be able to spend more on luxuries such as new computers, the latest technology gadgets, vacations, additional cars, and homes increasing private demand through consumption and investment. This is potentially why the Credit Impulse measure (new credit introduced to the economy through the banking system) tends to move contemporaneously with private demand (See Table 1). Another way to say this is that the balance sheet always shows the future income, so by following the balance sheet rather than solely focusing on the P&L, in this case, a flow metric such as GDP, you may be able to spot trends before the P&L is reported.
Several factors affect consumer confidence, including house prices, unemployment rates, and inflation. Falling house prices compromise wealth accumulation and erode consumer confidence. Increased unemployment rates also negatively affect consumers’ confidence in the state of the economy. Inflation is an indicator of too much economic growth, and the rise in prices can reduce consumers’ purchasing power and confidence. It has always been difficult to estimate the magnitude of the wealth effect because changes in asset prices rarely occur without other macroeconomic changes.
Table 1 – Private Aggregate Demand vs. Credit Impulse – United States – 1976 to 2021
In countries that rely primarily on consumption to drive economic growth, the wealth effect is pretty significant to continue to drive economic growth forward. Debt plays heavily into the wealth effect as we shall see. Based on various Central Bank research, each dollar increase in asset values (risk assets such as real estate and corporate equities) is estimated to increase consumer spending between 3-5%. For advanced economies, consumption is anywhere between 50-70% of GDP (see Table 3 by country).
Although theories that highlight the role of wealth in determining patterns of consumption do not usually imply different effects for different types of wealth, there are many reasons to believe that the marginal propensity to consume (MPC) 1 from housing wealth and stock market wealth could be different. It is thought to be stronger for housing wealth, partially due to a higher proportion of the population holding their net wealth in housing. Also, the distribution of wealth within a country may impact the marginal propensity to consume, as less wealthy citizens may spend more of their income on consumption relative to more wealthy citizens may have the propensity to save more of their income rather than consume it.
Capital gains on wealth resulting from owner-occupied housing may lead to a higher MPC since these gains have a tax advantage over stock market gains in some countries.
The distribution of wealth or wealth inequality within the economy may impact the ‘wealth effect’ if a large share of wealth is held by the top 1%, given there are limits to consumption of this group relative to the rest of the population and hold less of their wealth in real estate, which may have large implications from a perspective of financial stability and interest rates. More on this later….
Consumption by households is generally higher in the US at almost 70% of GDP given high disposable income as well as usage of consumer credit. As a result of high consumption, the US runs a large trade deficit with the rest of the world through imports of durable consumer goods (washing machines, automobiles, and furniture), as well as nondurables such as gasoline, groceries, and clothing. Consumption includes spending on domestic services like real estate and health, cable, and internet services which account for about 2/3rds of consumption. Retail Sales are a great barometer for consumption, as well as consumer confidence. If people are confident (grey-line) as their home values (blue-line) is increasing in value, they are more likely to spend now (orange-line) (Table 2).
As home values rise, homeowners find it easier to borrow using their home value as security for either home renovations or consumption spending. If this ‘wealth effect’ is strong, it could leave the economy more vulnerable to adverse events, such as a large decline in house prices. We can see in the run-up to the 2007-2008 recession in Table 2 home equity extraction was potentially being used by households to finance spending, and the combination of the pullback in house prices as well as job loss reduced consumption significantly in 2007-2008. We see in 2020-2021 a similar trend of housing/consumption moving together – well above trend. Historically, large price increases well above trend have resulted, in large declines, including a reduction in household spending. Hence too much reliance on residential real estate and the wealth effect/consumption could have issues for some countries’ financial sustainability going forward. We plan to cover this in a future post.
Table 2 – Personal Consumption Expenditures (PCE), Confidence Surveys, and Real Estate
Table 3 – Consumer Spending, Allocation of Wealth between Housing and Stock Market
1. Income inequality scale = Gini coefficient, 0 = complete equality and 1= complete inequality.2. Closer to 1 = Greater Wealth Equality, further away from 1 = Less Wealth Equality. 3. Indicators include housing expenditures as % of total expenditures, Dwellings with basic facilities, Rooms per person.
In Table 3, we lay out a few summary metrics for a selection of OECD countries – Europe (France/Germany) and Anglo-Saxon (US, UK, Australia, and Canada). We note the following:
Housing is the principal source of household wealth in most countries and homeownership reduces wealth inequality. High homeownership countries tend to exhibit lower wealth inequality.
Mortgages represent the largest part of household debt. House prices have increased faster than income in most countries as housing supply has not kept pace with demand and structural elements such as tax policy and regulation tend to favor capital investment/risk-taking relative to labor income. Historically capital investment has driven higher productivity leading to greater economic growth. Having such a disproportionately large residential investment sector relative to the size of the economy can create problems as though it may provide short-term growth when the house is built or when the house is sold, it is considered non-productive investment, as it does not provide future growth to the economy continuously.
Real Estate (if financed by debt) diverts money to be spent on debt service which could have been invested in a business. This business may support the community and provide additional jobs. Government involvement through the secondary mortgage market may increase the supply of credit (i.e. implicit guarantee in the US by government-sponsored entities) and have led to misallocation of too much capital into real estate historically – see Table 4 for other government involvement in mortgage markets. During the Great Financial Crisis, 40% or so of loans went to people with a poor ability to service them – sub-prime and low documentation of income borrowers. And many were non-recourse loans – so borrowers could just hand over the keys to the house if its value fell. This was encouraged by a public policy aimed at boosting home ownership and ending discrimination in lending. You will note that in Table 4, only the US has non-recourse loans.
Table 4 – Key Country-level programs to support mortgage borrowers
Generally speaking, modernizing the economy through enhanced productivity, and reducing wealth and income inequality by boosting homeownership and housing values (i.e. wealth effect) has led to the higher marginal utility of underlying citizens as measured by OECD Better Living Index (Canada and Australia).
Property taxes collected by the government also rely on housing retaining value over time and represent about 3% of GDP on average. However, taxes on personal income are roughly 3-4 times property taxes.
Wealth inequality arises from the way capital is accumulated. Labor and capital are both inputs into the production process, but the income received by workers and capital-owners likely accrues to different economic classes of people
Higher-income/wealthy citizens tend to own their homes outright (i.e. no mortgage) relative to lower-income citizens and tend to have a higher proportion of financial assets (stocks) – owners of capital (see Table 5) either through savings or acquired through compensation plans.
Since returns on capital (dividends, interest, and capital gains) based on corporate profits, are a major source of income for the wealthy citizens, and capital tends to grow faster than wages, the rich become richer, as they save more than they consume. This theme is consistently observed across the globe and across time. Generally, returns on capital or profits are associated with a combination of innovation, risk-taking, and ownership of capital and intangible assets (machines, servers, etc).
You will note that returns on capital have risen, as returns on labor (wages) have fallen over time. Low-wealth citizens tend to rely on wage income, have very little savings and rely on higher levels of consumer debt relative to income to fund consumption. In the case of the US, the share of GDP of capital relative to labor has dramatically changed over time and accelerated in the unanchored credit-based system, particularly after 2000 (See Table 6) with the flood of labor supply with China and other former communist countries joining global trade, as well as technology change/automation. In the case of the US, over the past 30 years, corporate equities of the Top 1% of the wealth distribution have increased significantly to 48% of assets as compared to 18% in 1989 (see Table 7). Similar trends have been observed across other western countries as tax policies have generally favored capital investment over labor and unions which protected the labor share previously have been in decline since the 1970s.
Table 5 – OECD Average Wealth Distribution by Type
Table 6 – Labor (LHS) and Capital (RHS) as % of GDP – United States
Table 7 – Balance Sheet by Wealth Distribution – United States
Low-wealth households have much higher debt, of which property debt is the main form but consumer debt (e.g. credit card debt and installment loans) represents almost 30% of total household debt by the bottom 40% on the wealth distribution. While consumer debt can help support economic growth for consumption, it could also be a sign of stretched living standards which leaves those households exposed to future financial shocks. We noted a similar pattern in the US as shown in Table 7.
While higher-income households tend to have higher debt loads, debt payments as a proportion of household disposable income are larger for lower-income households. We tend to watch changes in debt-service ratios and changes in interest rates rather than output gaps (Real GDP vs Potential Real GDP or unemployment gaps) alone as a determining factor of the changes between business cycle – growth and recession, given the level of debt within the economy held by a large proportion of the population in most countries. More on this later..
We have noticed a recurring pattern reviewing runs to 2000, 2008, and 2020 recessions in the US. When real rates rise above long-term equilibrium real rates, private debt-service (households and corporates) levels tend to increase above trend reducing the growth rate of the economy (debt too high relative to cash flows), and in a high debt economy, interest rates need to be lowered or fiscal stimulus provided directly to indebted customers as we saw during COVID-19 in 2020. More on this in section 6.
Despite having the highest net wealth per household which has grown substantially over the past 40 years, in the US wealth and income inequality are substantially higher than all the countries above at least 2x in every category from both a wealth and income inequality perspective.
In Table 8, we show how wealth is distributed across the select economies and note that most are generally distributed similarly, with the US as the outlier. We note that the top 10% have increased their share of total wealth to 70% from 61% in 1989 (Table 7) in the US. A high concentration of wealth can have major social, economic, and political impacts.
The concentration of wealth/incomes also creates disproportionate political power for wealthy members of society who are able to influence the policy process
Stagnant labor income (which we have seen over the last 30 years) is harmful in times of weak aggregate demand, since income gains that are concentrated at the top of the wealth/income distribution, are less likely to fuel consumption and aggregate demand.
Over the last 10 years, we have started to see the outcome of this inequality through greater political polarization and populism play out.
Long-duration risk assets (such as stocks and real estate) have benefited households from the reduction in the real interest rates over the past 40 years (real 30-Year Treasury yield (orange-line) in Table 9 which is thought to be due to lower working-age population, higher saving rates, as well as actions taken by the Central Banks related to lowering short-term rates and Quantitative Easing.
This has increased the select countries’ average household’s net wealth relative to disposable income by 1.5x from 1995 (Table 9) but has also increased wealth inequality, particularly benefiting the top 10% of wealth who hold financial assets such as stocks in the US (green-line). It has also increased debt as well.
Quantitative Easing (QE) is a policy tool that has allowed Central Banks to more directly influence those longer-term interest rates that consumers and businesses pay. Under QE, a central bank buys government bonds. By buying government bonds raises their price and lowers their return-the bond’s yield. QE sends a signal that Central Banks intend to keep the policy interest rate low for a long time—as long as inflation stays under control. By giving more certainty that the Central Bank policy interest rate will remain low, QE can help reduce longer-term borrowing costs for businesses and households.
Many businesses have taken advantage of the lower cost of borrowing and repurchased their own shares in the open marketplace with lower-cost debt. Over the last decade, buybacks have tripled often to obtain the desired leverage target or debt as a percentage of assets. Firms desired leverage can be excessive if companies do not consider all financial distress costs through the cycle and therefore these costs may shift to creditors or the public through potential bailouts. These actions may have also provided additional returns on capital to households higher up in the wealth distribution as well. Excessive leverage may be a financial stability concern as well.
Table 9 – Net Wealth to Disposable Income
The other side of the higher wealth coin is higher debt. This is a very important concept and will be discussed in the next series of posts. It is also important to recognize where the debt sits in the overall wealth distribution of a country and who owns the debt/is financing it within this distribution. In Table 10, we note that total debt (grey-line) within the economy at both private (households and corporate) and public (sovereign) debt has grown by 1.4x similar to wealth (blue-line) of 1.5x. You can see from the rolling compound annual growth rates for net worth, private credit and money supply, these three elements are very much intertwined and related to the wealth effect concept. We will cover this concept throughout the next series of posts. Remember, each time a bank creates a loan, a corresponding deposit is created through the banking system, which adds to the money supply. There are limits to how much money a banks can create which are imposed by various regulations and also depend on demand for loans at the existing interest rates. We have also seen governments create money via the Treasury by directly transferring funds to household bank accounts during COVID-19 situation (and running significant fiscal deficits, which are large monetized by the central bank through buying up the issued bonds) which is included in the money supply. This is very high-powered money and allows an economy to recovery very quickly from a shock and does not have the lagged effect of lower interest rates. These actions are consistent with views proposed by some economists that call for fiscal authorities to rely on greater fiscal spending/borrowing such as Modern Monetary Theory or Universal Basic Income, which may be used to partially redistribute spending back to lower wealth/income households. The flip side of increasing fiscal spending is that associated above target inflation that many countries have seen in response to COVID-19 fiscal stimulus, coupled with supply chain shocks.
Table 10 – Private Credit (LHS), Money Supply (LHS) and Net worth (RHS) – United States
However, the growth in overall wealth and increase in inequality may have driven down the cost of capital as more money is available in a credit-based system to invest in capital (debt or equity), this may have increased risk-taking due to lower expected returns across all assets and the incentives for outsized wealth have driven substantial investments in technology and innovation supported by capital markets (see Table 11). More on this later….
Table 11 – Increases in Technology and Innovation (% of World Patents)
2. How Credit Contributes to Economic Growth
Before we jump into the drivers of asset prices over various debt cycles, let’s take a look at what drives economic growth. Generally, there are three ways to increase an economy’s GDP over time using the Cobb Douglas production function:
Labour + Capital + Total Factor Productivity = GDP growth
Labor = number of person-hours worked to produce a good or service
Capital = invest in a capital good – machinery, equipment, buildings
Total Factor Productivity = More output per inputs of labor and capital
Households may work more hours to obtain greater disposable income to be spent or saved. Capital may be invested in a business to generate a profit. Earlier we have discussed how the labor share of production has been declining over time. Increased productivity may come from automation to produce more output.
In Tables 12-13, we have shown the growth in the working-age population over time and how the growth in labor and increases in productivity have historically driven economic growth in the US. As growth in labor is expected to decline from 0.4% to 0.2%, if higher productivity is not achieved, then real GDP growth will be lower than what we say today which is roughly 2.0%.
To offset the decline in labor growth, the ‘wealth effect’ looks to optimize the above equation and brings forward future consumption and investment as credit provides additional purchasing power in today’s economy for the future promise of repayment along with interest payments along the way.
Table 12– Growth in the Working-age Population
Table 13– Drivers of GDP Growth – United States
Debt lets households smooth over income shocks (i.e. illness, short-term unemployment) and invest in high-return assets such as housing or education, raising average consumption over their lifetime. Credit demand may increase as households may be optimistic about income prospects or low costs (i.e. interest rates are low). As mentioned earlier, the largest debt on consumer balance sheets (Table 14) are mortgages representing about 65% of total liabilities by U.S. consumers used to fund the largest asset on most households’ balance sheets – Real Estate –which we will cover in the next section. However, to understand the ‘wealth effect’ in greater detail and who benefits from it, in Part 2, we intend to dig deeper and construct balance sheets by wealth distribution to understand how wealth is created in America and where the debt that is used to create this wealth resides.
Structural factors such as demographic changes or population growth/immigration are expected to drive credit demand, also contribute to an increase/decrease labor in the production function.
Table 14 – Aggregate Consumer Balance Sheet – United States
3. Given that for most countries’ citizens’ residential real estate are the largest source of net wealth and is the largest source of the ‘wealth effect’, what are the main drivers of house prices in Advanced Economies?
House prices in many advanced economies have risen substantially in recent decades. But experience indicates that housing prices can diverge from their long-run equilibrium or sustainable levels, resulting in a financial crisis like we would have seen in the Great Financial Crisis given that a significant amount of leverage is used in financing residential housing. This is why it is very important to understand the credit cycle in our credit-based financial system… more on this later. So monitoring house prices and understanding the fundamental drivers of home prices, along with macro-prudential regulation related to banking/mortgages has become more important as total debt in the economy has increased.
Let’s take a look at the fundamental drivers of residential housing pricing over time.
In Table 15, you can see there is a correlation between the growth in disposable income, home prices, and the number of housing units/population growth.
Table 15 – Real House Price Growth vs. Growth of dwelling stock vs. Growth of real disposable income vs. Population Growth since 1990 (per annum (%))
In a recent working paper, the International Monetary Fund (IMF) has broken down demand and supply factors which gives us a good framework to work from:
Household disposable income plays a key role in shaping house price trends – either from capital or labor share.
Household net financial wealth also appears to be a determining factor of house prices
Housing demand has also been fueled by declining interest rates
Demographic trends reinforced the high demand for owner-occupied housing (population growth and net migration to certain countries)
Undersupply conditions of housing can also contribute to housing price gains outpacing incomes
Tax incentives for mortgage financing and homeownership, which reduce the user cost of housing, can contribute to high and rising house prices. This favorable tax treatment on housing investment may crowd out capital from more productive use than housing and encourage excessive leverage.
Tax on Property is a significant source of revenue for governments. Most of the revenues from recurrent taxes on immovable property are assigned to local governments. Even in countries in which there are three levels of government, local governments tend to get the largest share.
In addition to the items highlighted by IMF, other supply issues for housing independent of credit may include land-use governance such as green space around cities, which reduce the responsiveness of supply changes to demand changes for housing. Government involvement through the secondary mortgage market may increase thesupply of credit (i.e. implicit guarantee in the US by government-sponsored entities).
Credit supply and credit cycle (interaction between borrowers and lenders and changing risk perceptions) are also very important to housing prices which we will look to cover next.
Also, given the financial liberalization over the past 40 years, foreign buyers may drive local real estate demand and some may view housing assets as a safe haven (like an inflation-adjusted bond). An increasing number of national and local authorities in countries such as Canada, New Zealand, Australia, and Hong Kong have imposed restrictions on foreign buyers, basing their policy action on anecdotal reports of substantial purchases by foreign Chinese buyers.
Stay Tune for Part 2 of The ‘Wealth Effect’ and Debt in which we will cover:
How does Debt impact the Wealth Effect?
Why is understanding Credit Cycles and Business Cycles are Important – A Review of the US – 1975 to 2021?
Why are Interest Rates and Debt-Service-Ratio Important to Watch for an Economy reliant on the Wealth Effect/Debt Growth?
Appreciate any questions or feedback you have or other research topics you may suggest.
This post is Part II of our Copper/Gold Ratio series. The Copper/Gold Ratio plays a significant role within the BT Market Risk Indicator and gives us a read on the day-by-day cyclical economic activity. We covered the macro drivers of Copper in our previous post.
In today’s post, we will cover the cyclical/structural drivers of the Gold price, as well as examine if Decentralized Cryptocurrencies such as Bitcoin or Ethereum (or Ether) may have replaced gold as a safe-haven asset and/or will protect investors against fiat monetary inflation/currency debasement.
We will cover the following sections:
History of Gold Usage in the Financial System
Demand and Supply of Gold
The Golden Rule! Our Current Financial World Order
Have Cryptocurrencies replaced Gold as a Store of Value?
BT Machine Learning Models – Gold, Ether, and Bitcoin
1. History of Gold Usage in the Financial System
Gold has benefitted from diverse sources of demand: as an investment, a reserve asset, jewelry, and a technology component. It is highly liquid, has no one’s liability, carries no credit risk, and is scarce, historically preserving its value over time. It is a store of value. Gold has been the ultimate safe-haven asset to withstand economic recessions, inflation spikes, and credit risk concerns. Central banks have been net purchasers of gold since 2010, ending a multi-decade streak of net gold sales that had persisted since the end of the Bretton Woods system in the early 1970s. Investors tend to sell copper and invest in gold in times of economic/geopolitical crisis and hence the Copper/Gold Ratio declines.
The open secret in the financial world (in a fiat currency world order) is that governments discourage the use of gold as money for their citizens and promote its use of fiat currency through the banking system, but they hold in it through their reserve assets at their central banks. Alan Greenspan once said deficit spending (or debt-driven growth) is simply a scheme for the hidden confiscation of wealth (via inflation). Gold stands in the way of this insidious process. It stands as a protector of property rights. Generational memories of high inflation and how the value of paper currencies can be destroyed, generational memories of war, and upheaval (i.e. Germany) have driven the importance of gold in times of crisis and emergency.
Three Monetary Systems have Lasted Multiple Millennium
For thousands of years of human history there have been 3 different monetary – see Table 1 as Ray Dalio has covered in his book The Changing World Order – Why Nations Succeed and Fail. When the country needs more money/credit to deal with debt or fund wars or respond to a pandemic or crisis, it will move from Type 1 to Type 2 or Type 2 to Type 3 so that it can print more money and devalue the currency including reducing interest rates against real assets which may have different levels of relative scarcity such as real estate and commodities (i.e. resulting in increases in nominal value).
If too much debt is created in the Type 3 currency (i.e. fiat currency) and trust and credibility of investors and citizens fall, and investors and citizens will get out of cash or spend it quickly as it no longer functions as a store of value. To regain creditability the currency would need to move from Type 3 into a Type 1 which is backed by hard assets (i.e. gold or silver) or a commodity with limited inflation or high scarcity. China the country that invented the world’s first fiat currency has moved back and forward between the different monetary systems over the last 1500 years (see Table 2 below).
Table 1: Different Monetary Systems – Hard Money to Fiat Money
Table 2: Transitions across Different Types of Monetary Systems in Chinese History
Back to the current financial system and US dollar reserve currency regime as we have seen similar themes play out. Before 1971, foreign currency reserves were effectively backed by gold (a Type 2 system), either directly under the gold standard or indirectly through the US dollar standard.
Despite the severing of this link in 1971 (Type 3 system), the US dollar and US Treasuries backed by the full faith and credit of the United States has continued to play a central role in the international monetary system during the latter part of the 20th century due to the country’s economic strength and the stability of its political and judicial system.
The key factor to driving gold prices since 1971 has been the lack of debasement via inflation as annual supply growth of gold (above ground stock) which has been about 2% per year relative to money supply growth of 6%…more on this later. Gold’s scarcity relative to fiat currency derives its value.
Fiat money can be printed in unlimited quantities to support monetary policy, as exemplified by the quantitative easing measures in the aftermath of the Global Financial Crisis (GFC). In recent years, the rapidly increasing global money supply and a low to negative rate environment have fostered an optimal environment for gold to outperform global sovereign debt, such as US treasuries, and track the global money supply. Gold has been more negatively correlated with equities in extreme market selloffs than commodities and US treasuries. As a result, gold is viewed as a safe-haven asset as a hedge against equity market drawdowns, and currency/sovereign bond devaluations/defaults.
Table 3: Gold vs. M2 Money Supply
Sanctions and US dollar payment system
The US dollar’s global dominance gives the US a powerful tool to enforce sanctions on people, institutions, and countries. The pervasive nature of the US dollar payments system along with its dominance in international transactions has enabled the US broad powers to impose economic and financial sanctions on other countries.
The US has enforced sanctions by restricting foreign governments, institutions, and individuals from using US dollars in international financeso that they are unable to receive payments for exports, pay for the purchase of goods, or own US-dollar denominated assets. Some view this as weaponizing the US dollar which started under the Clinton administration in the 1990s.
Central Banks in countries that have been threatened with sanctions (i.e. Russia, China, Iran, etc.), have begun to hold higher gold reserves, so that they may continue to make payments by circumventing the US dollar payment system and these sanctions. These sanctions may have also led to further strategic alliances (Russia, China, and Iran) and trade agreements which may weaken the USD system in the future…more on this later. Private decentralized cryptocurrencies have also been used to move money outside of the US dollar payment system and sanctions as well.
Gold Investment Characteristics
Credit (or default risk) and negative real rates sustained over a long period are the largest risks faced by bond investors. Gold provides a safe haven to investors with the following characteristics (see Table 4).
Over the last hundred years, many countries even those thought to be safe, and liquid for bondholders, have experienced sovereign debt defaults (see Table 5), resulting in permanent loss of capital. Gold is held in central bank reserve assets as it is the only asset free of default risk.
Table 4: Gold Investment Characteristics
Correlation with other assets 0.1 on average
Effective Tail risk hedge including sovereign debt defaults and restructuring
Liquidity higher than German bunds, British gilts, US Treasuries
Negative correlations with fiat currency, especially with USD
Performs well rising price inflation and strongly in deflationary times
Table 5: Notable Sovereign Debt Defaults and Restructurings
2. Demand, Supply, and Reserves of Gold
Now that we’ve looked at the history of gold in the monetary system, let’s take a look at some of the structural drivers of demand and supply of gold and where it is locally from a geographical perspective. Demand comes from 4 main areas – Jewelry, Technology, Investment, and Central Bank reserves with a significant demand coming from emerging markets led by China and India representing about 50% of overall world demand (see Table 8). Structural growth drivers are at play here as highlighted in Tables 6 and 7.
Supply is mainly driven by mine production and recycling of gold (see Table 9). Mine production tends to grow at roughly 2% per year (similar to the inflation target for Central Banks around the world) which may be a legacy holdover from the Type 2 monetary system in 1960/the 1970s.
Table 6: Global Market Demand for Gold 2010-2021
Table 7: Gold Structural Drivers
Table 8: Demand Geographically Diverse but skewed more towards Emerging markets (China and India) representing 50% of the global demand
Table 9: Global Gold Supply – Increases about 2% per year
Table 10: Consumer Demand and Mining Production by Country
Though the global monetary system is in Type 3 (no backing by commodity), gold still plays a significant role in reserve management for the central banks, representing upwards of 60% of total foreign exchange reserves for advanced countries such as the U.S., Japan, and Europe.
The top 20 countries that hold gold in their Central Bank portfolios represent about 85% of total gold held by central banks globally, Central Bank reserve managers highlight gold’s performance during times of crisis as to why they continue to hold in their securities portfolios – see Table 11.
You will notice that the US holds 23% of global central bank gold, which is consistent with GDP as % of Total World GDP, however, is much less than the 70% of world supply at the Bretton Woods, yet continues to yield significant control of the financial system as much of trade is done in US dollars.
Table 11: Central Bank Reserves – about 20% of Total World Gold Supply
Table 12: Central Bank Reserves – Performance in Times of Crisis top reason to hold gold
Heightened economic and political risks – Central Bank FX Reserves
Central Banks are heavily exposed to the risks associated with advanced economy debt including:
The long-term impact of the COVID-19 pandemic on monetary and fiscal policies
Rising global inequality, which has fueled social unrest and the rise of populist parties
Greater polarization of political parties, which increases the likelihood of large policy shifts from one administration to the next
Deteriorating budget positions and aging populations
Growing trade disputes and protectionist policies
Increasing challenges to central bank independence around the world and the threat of sovereign debt being monetized
An increased threat of competitive currency wars.
Anticipation of changes in the international monetary system
Structural factors also seem to underlie central banks’ interest in gold including the following:
Economic power is shifting from West to East and gold is moving in this direction. China is now the world’s largest economy on a purchasing-power-parity basis. It is the largest trading nation in the world and has the third-largest sovereign debt market.
In recent decades, China has become a key driver of global growth, and is expected to play a major role for years to come. We note that gold is also flowing from West to East from dominant powers to emerging powers. We have seen this type of outcome playing out in previous changes to the monetary system – Dutch to British and British/US – see Table 16 – Lifetime of Empires.
The reconfiguration of the global economy and China’s rising global footprint is expected to have an impact on the international monetary system. China has already taken steps to internationalize its currency by introducing several measures to promote renminbi cross-border settlements. More on this in the Golden Rule section.
China’s Impact on the Gold Market
Over the past two decades, China has become the world’s leading gold market. As both the largest gold consumer and producer in the world, China plays a key role in the global gold market. Despite being the world’s number 1 gold miner, it relies on imports to meet local gold demand. Approximately 60% of China’s annual gold supply is sourced from imports and western markets have played an important role, as they account for roughly 50% of the imports.
In Table 13, we show the process in which gold goes from mining to the UK (largest importer of gold via London Bullion Market Association or LBMA) for trading and on to Swiss refineries to end-user demand in China. LBMA sets Good Delivery standards for trading contract settlement (400 troy ounces). London is by far the largest global center for Over-the-Counter (OTC) transactions followed by New York, Zurich, and Tokyo. LBMA accounts for roughly 45% of global gold market liquidity. Western markets control much of the global gold market liquidity through the combination of the COMEX (NY) and LBMA and North American ETF trading represent about 80% of global gold market liquidity as of January 2022.
China’s major import markets are Australia, the UK, and Switzerland. The UK is also the world’s largest importer of gold and is Switzerland’s 2nd largest trade partner with respect to gold. Australia, the US, Canada, and Mexico have significant gold mining and reserve capacity and are net exporters of mined gold traveling through the UK and Switzerland, at almost 600 tonnes annually, satisfying Chinese and Indian consumer demand for gold. The general trend has been gold has been moving from West to East over the last 30 years. (See Table 14).
Table 13: Transportation from Western Market to China
Table 14 – Select Western Market Global Net Exports of Gold – 1994 to 2020
India’s Impact on the Gold Market
The drivers of gold demand in India are many and varied. Cultural affinity, long-held tradition, and festive gifting play a significant role. With India’s deep affinity for gold, Indians have historically turned to this asset as a means of preserving their wealth – and increasing its value over time. However, India is unusual. Even though the country is one of the leading sources of gold demand worldwide, there is almost no domestic production, as almost 90% of India’s gold supply is imported. As such, when demand rises, imports tend to rise in sync. This can, at times, have a significant effect on India’s trade balance and current account. India generally speaking, imports from Western markets via Switzerland and Africa via UAE and Ghana.
Most of the gold produced in the world transits physically through Switzerland, and in particular Ticino. Four of the world’s major refineries of gold are located on Swiss soil. In an average year, Switzerland refines about 70 percent of world gold.
United Arab Emirates
As late as 1996, the UAE did not even appear among the world’s top one hundred gold-importing countries. Two decades later, the UAE ranked among the top four, above Hong Kong and the United States. The customs data provided by governments to UN Comtrade, a United Nations database, shows the UAE has been a prime destination for gold from many African states for some years. Dubai’s role as a financial center and its lax regulation of the gold trade, favorable geographic position between Asia and Africa, and access to free trade zones have all contributed to Dubai’s growing reputation as a node of corruption.
Concerns about Dubai’s role in the illicit bullion trade have grown in recent years after reports that regulatory loopholes allow gold linked to conflict and money laundering to trade there. The city is the destination for 95% of the gold originating from east and central Africa, according to United Nations data, and that region is considered high risk due to the presence of armed groups.
Now that we have covered the structural drivers of demand and supply on a worldwide basis, let’s take a look at Gold’s influence on financial markets and the current world order.
3. The Golden Rule! Our Current Financial World Order
The first Golden Rule is the principle of treating others as one wants to be treated. However, when we talk about the world order/financial system and look back at history, whoever has the gold makes the rules.
A lot of the architecture and imbalances via trade in today’s financial system can be traced back to the choices made at the end of World War II and the relative positions of the countries back then. It was clear during World War II that a new international system (“Bretton Woods”) would be needed to replace the Gold Standard after the war ended. Let’s review how we got to where we are today.
Type 2 Monetary System – Bretton Woods: The design for it was drawn up at the Bretton Woods Conference in the US in 1944. US political and economic dominance necessitated the US dollar being at the center of the system. The massive 20,000 metric tonnes of gold accumulated by the US Treasury (roughly 70% of the world’s gold supply) at the time provided confidence in the success of the Bretton Woods framework. The Bretton Woods system was drawn up and fixed the US dollar to gold at the existing parity of US$35 per ounce, while all other currencies had fixed, but adjustable, exchange rates to the US dollar. Unlike the classical Gold Standard, capital controls were permitted to enable governments to stimulate their economies without suffering from financial market penalties. The dominant power at the time of crafting Bretton Woods, the UK, and British Pound Sterling was the world’s reserve currency, however, the UK was on its downward arc, in its lifetime as an empire – see Table 16 for further information.
A couple of summary facts of relative positions of global powers at the time:
Held ~70% of the world gold
Used up all gold reserves during WWII
Largest Net Creditor – Lender of the Marshall Plan (repair infrastructure after WWII in Europe). Collectively-owned more foreign assets than foreigners owned US assets
Net Debtor – needed debt relief following WWII
US wanted to break UK dominance of world trade. Emerging superpower.
The UK was the lead trader at the time and the dominant military superpower. GBP was the reserve currency of the world.
Type 3 Monetary System – Petrodollar: In August 1971, President Nixon announced that the US would end on-demand convertibility of the dollar into gold for the central banks of other nations. The Bretton Woods system collapsed and gold traded freely on the world’s markets. USD maintained its supremacy as the world’s reserve currency through the petrodollar – see the last article for further information. The current system is backed by the full faith and credit of the US.
A Paradox – Fiat Currency, Credit Cycles and Gold in a Type 3 Monetary System
So if gold is no longer at the centerpiece of the monetary system why do central banks continue to hold almost 20% of all of the world’s gold ever mined? A simple answer, the fiat currency system can be volatile as a result of credit cycles, and gold has performed well historically as a safe-haven investment in times of crisis.
Conceptually, gold is linked to the end of credit cycles. Credit cycles start with the monetary authorities. When the money supply is inflated and interest rates lowered artificially, naturally unprofitable projects appear profitable, the structure of production is overdrawn, and more debt is taken on. Money is created through the credit creation process through the banking system. As a credit cycle ends, the unprofitability of many of these businesses becomes apparent as they systematically fail to meet their projected performance. This often results in mass liquidations, layoffs/unemployment, and recession. To offset the lower amount of private credit creation during the recession, sovereign debt is issued to reduce the time a country may spend in recession by bringing debts and interest payments back in-line with cash flows. See Table 15 to see how this has played out over time in the US.
Consequently, investors grow concerned about volatility during a recession, and gold frequently rises in value. Gold is the store of value in a credit-based system.
The rules of the credit-based system are documented and applied through the Basel Framework via the Basel Committee on Banking Supervision (BCBS) which aims to strengthen the regulation, supervision, and risk management of banks globally. The BCBS was created in 1974 (around the time of the movement to the Type 3 Monetary System) and comprises central banks (i.e. who hold the gold) and bank supervisors from 28 jurisdictions.
These rules maintain the current system and create fiat currency via the credit creation process. The rules also provide a large number of buyers (i.e. banks) for sovereign debt held as high-quality liquid assets (HQLA) in their liquidity portfolios and considered the most liquid and are of the highest quality in times of stress.
Table 15 – U.S. Business Cycles – Debt is higher and Interest Rates are lower each cycle
Let’s fast forward to the current day. We see that the architect of the current regime continues to benefit from the exorbitant privilege the US dollar has afforded, however, times have changed for the US and appears to be on the downward slope of its arc which many reserve currencies experience given the buildup of excess debt in their systems – see Table 16 below.
Table 16: Lifetime of Empires
We see that after operating in the Bretton Woods system, the collapse and subsequent emergence of Type 3 monetary system, Great Financial Crisis (GFC) and COVID-19 Crisis, in Table 17 we note that the US looks very similar to the UK after WWII and China appears very similar to the emerging US power after WWII.
Table 17: Lifetime of Empires – Reflecting on Emerging Power and Dominate Power (Current Day)
May control 65% of the world’s gold via strategic alliances (see below) and appears to have amassed 20,000 tonnes of gold (similar to the US in Bretton Woods world order).
Holds about 20% of the world’s gold
Net Creditor – Lender of the Belt and Road Initiative which represents the largest project of its kind globally comprising 60-70% of the world’s population.
Japan and Germany are also net creditors.
Net Debtor – potentially need debt relief following COVID-19 or will run negative real rates to inflate away the debt. Widening trade deficit.
China has broken US dominance of world trade and wishes to de-dollarize via digital RMB and build infrastructure and trade routes through Belt and Road Initiative. Emerging superpower.
Outsourced a large portion of its manufacturing base when compared to peers such as Japan and Germany. Dominant military superpower. No longer dominate trade position. COVID-19 demonstrated weakness in the supply chain. The US Military will continue to enforce the US Dollar’s use as the Global Reserve Currency
De-dollarization one commodity at a time – Internationalization of the Renminbi (RMB) and possible linkage to gold?
We note that through the lifetime of empires, through the downward arc, the dominant superpower usually loses its exorbitant privilege (run twin-deficits) via reserve currency status (i.e. weakens as a result of excess debt as compared to productive capacity). We have covered in earlier posts, that over the last 20 years there has been a decline of US dollars within the FX reserves of global central banks, however, remains at ~60% of reserves currently (far greater than the US GDP as % of World GDP). We are seeing further de-dollarization via trade agreements (albeit slowly) and expect to see this continue going forward.
China is the largest importer of oil. We are starting to see de-dollarization in oil being priced in renminbi (yuan). A significant boost to the internationalization of the RMB has been its use in trade in oil, with countries like Russia, Iran (China’s two most important oil suppliers), and Venezuela already accepting the RMB payment for oil deliveries, and China making the yuan more attractive by ensuring that it is fully convertible into gold on the Shanghai and Hong Kong markets. This is another significant step toward de-dollarization – the slow but steady move from a system with a single world reserve currency to a multipolar world in which the euro and yuan play supporting roles alongside the US dollar.
China is pursuing several goals at once: developing its financial center; strengthening its currency, the renminbi (yuan), in international trade; and expanding its economic dominance in Asia. The aim is to gradually bring the renminbi on a par with the US dollar and the euro. This goal is a long way off; as only a very small part of international reserves held by Central Banks is currently held in the RMB (Chinese national currency) at around 2% which is equivalent to Canada which has 1/8th the size of the economy.
However, China has improved its position through clever maneuvers in the oil and gold trade. Let’s review what has occurred:
2013: China no longer accumulates US bonds in its central bank reserves. Currently holds about $1 trillion or 4% of total US Treasuries outstanding.