The stock market is a complex system that tends to get oversimplified by investors and analysts alike. Some generalities get repeated ad nauseam causing the average investor to accept them as fact. This article investigates three such generalities and shows why they do not stand the test of statistical or theoretical analysis. Lastly, given this knowledge, I recommend an all-weather portfolio that provides adequate diversification, using portfolio hedges, and investing with a value mindset that limits downside risk.
Myth #1: Bonds Always Move Opposite Stocks
U.S. Treasury Bonds serve an important function in the portfolio by preserving capital during times of crisis. Yet the idea of bonds as a perfect hedge simply does not hold weight. The chart below shows the history of stock vs. bond correlations from 1927 to 2013. According to the PIMCO study that produced the chart, stocks and bonds have an average correlation of 10% with a high standard deviation of 40%. Correlations can range from as high as 86% as they did in 1993, or as low as -93% as they did in 2011. Therefore, correlations swing wildly but remain positive on average.
The study concludes that the macroeconomic regime determines the correlation of stock and bond prices. Here's the conclusion in their own words:
This analysis challenges conventional wisdom for asset allocation. Over the last 15 years, many investors have been able to ignore inflation risk and have taken for granted the very negative correlation between stocks and Treasuries. In the next decade, particularly in light of aggressive and expansive central bank monetary policy, the importance of the inflation risk factor may indeed resurface. If so, many of the correlation dynamics that investors have become accustomed to may be less relevant.
Recency bias has caused most investors to assume that stocks always move opposite bonds. In a macroeconomic regime shift of higher inflation or higher interest rates, these investors would see this assumption challenged.
Myth #2: Stock Markets Always Go Up in the Long Run
Jeremy Siegel's seminal 1994 book, Stocks for the Long Run, solidified the conventional wisdom of buying and holding stocks for periods of 20-30 years, as stocks have averaged 6.5-7% for the last 200 years. Siegel studies stock and bond returns from 1871 to 1997 (second edition). Yale endowment fund manager David Swensen argues that the study may not be as relevant as most investors believe. He states that for much of the time period studied, "the United States was an emerging market, the Federal Reserve System did not exist, and long-term government bonds were not available" (Pioneering Portfolio Management, p.110). A country that catapults itself from emerging market to global hegemon and creator/guarantor of a globalized free-trade economic system SHOULD see returns of 7%. Even then, the U.S. did not achieve this rate as fluidly as the lay investor may believe. For example, the stock market saw -0.4% compounded annual real return from 1966-1981 that's fifteen years of U.S. stock market stagnation.
Some global economies have, in fact, left their domestic investors worse off. The Tokyo Nikkei Average has yet to recover from its 1990 stock market high. The French CAC 40 Index also has yet to recover from its 2000 stock market high. That's 28 and 18 years of stagnation respectively (and counting). The United States does not have a bubble economy as poorly managed as 1980s Japan or the lack of growth faced by contemporary France. However, the U.S. has its fair share of economic issues that will prevent future growth.
(Source: author, stockcharts.com)
(Source: author, stockcharts.com)
To further explore this topic, let's take a look at the four factors of the production function: land, labor, capital, and entrepreneurship. In the land/natural resources department, the United States' onshore oil reservoirs have depleted by over 40 percent since 1970. Labor-wise, the population pyramid below demonstrates that the U.S. does not have the tailwind of millions of baby boomers entering the work force at the same time to create consumption-fueled growth. In fact, as the baby boomer generation retires, the federal government faces the mounting task of closing the fiscal gap of federal income to entitlement guarantees. Much of U.S. growth has derived from capital or debt. Yet debt-fueled growth faces the law of diminishing returns as the second chart below demonstrates. Simply stated, GDP growth generated per dollar of business debt (or federal debt for that matter) continues to decrease as more income goes to service previous debt. The U.S. needs more debt for less growth unless it actually begins deleveraging. Rule of law and a friendly business environment allows the U.S. to serve as a hub for entrepreneurship worldwide and I do not see this changing. However, the 1871-1997 U.S. stock market and the 1998-2124 market will face completely different sets of issues. The economy and the stock market should grow, but assuming 7% growth in perpetuity based on the historical average is textbook oversimplification considering these macroeconomic headwinds.
(Source: U.S. Census Bureau)
(Source: Mauldin Economics)
Myth #3: You Can Quantify Risk
Analyst's two most popular risk models are the Beta Coefficient and the Value at Risk Model. The Beta Coefficient indicates the volatility of a certain stock using its standard deviation, where a higher beta coefficient indicates more risk. The VAR Model also uses standard deviation to create a normally distributed bell curve. From this bell curve, investors can see the likelihood of potential returns as shown in the example below. Unfortunately, proponents of these models conflate risk and volatility. If a company's stock price drops by 50% in a short time period, that stock will be viewed as risky. When, in fact, assuming the fundamentals have not changed, this becomes a less risky investment because it now trades at a larger discount.
Long-Term Capital Management's over-reliance on risk models nearly jeopardized the global financial system in 1999. Leveraged 25:1, LTCM calculated the likelihood of a 1998-style crash as a 7-sigma event. For some perspective, "a 5-sigma event corresponds to an expected occurrence of less than just one day in the entire period since the end of the last Ice Age." 1987 and 2008 were considered 20+-sigma events. As Nassim Taleb states, that's once every "several billion lifetimes of the universe" (The Black Swan, p. 276) Quantitative models of risk that rely on historical standard deviations are comically flawed and better off ignored.
How to Take Advantage
If stocks and bonds have a positive correlation, a 60/40 portfolio does not constitute adequate diversification. True diversification involves owning several uncorrelated asset classes and hedging against high-risk events. Examples of other asset classes to own include emerging market stocks and credit, gold, real estate, commodities, and cash. Adequate diversification with hedges also serves as a solution to the idea that stock markets may stagnate for several years or decades. As one asset performs better in relation to others, simply rebalance accordingly. This strategy provides steady returns with muted volatility. An all-weather portfolio may not be as exciting as owning high-flying tech stocks, but as Paul Samuelson once stated, "investing should be more like watching paint dry or watching grass grow. If you want excitement, take $800 and go to Las Vegas." The all-weather portfolio generally tracks the benchmark S&P 500 Index, only significantly outperforming during times of U.S. economic weakness. Following this general strategy, while having a contrarian mindset to increase portfolio allocation to U.S. equities when the S&P tumbles should guarantee strong performance.
(Source: Star Magnolia Capital)
Additionally, I would recommend rethinking risk. Seth Klarman defines risk as 1) the probability of loss and 2) the potential amount of loss. The best way to avoid a probability of loss is to invest in healthy companies with stable balance sheets and no macroeconomic threats to earnings. The best way to minimize loss is to invest when the companies are trading at a discount to intrinsic value. When thinking about risk, preparedness trumps prediction. Do not rely on probabilistic models but instead rely on your ability to select good companies or assets at discounted values.
Disclosure: I am/we are long SPY, EEM, DBC.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.