5 important investing lessons from a leading academic
Professor Ken French of Dartmouth College co-authored research with Eugene Fama on the value effect and multi-factor asset pricing models which won Eugene the 2013 Nobel Prize for Economics (I still don’t know why Ken was not named as well and I have been reluctant to ask him!).
Ken recently spoke about his essay “Five Things I Know about Investing”, which addresses five principles he uses for designing a portfolio for anyone – especially himself. We have shared the key points from his essay below, all of which reaffirm what factors truly matter when investing.
1. Risk is uncertainty about lifetime consumption
Most investors are risk averse, but there is much confusion about what risk is. When I ask students and investors what risk means I get conflicting answers. Some say it is the potential for loss. Others suggest it is the volatility of the return.
I define risk as uncertainty about lifetime consumption broadly defined. People invest because they want to use their wealth in the future on things like food, shelter, travel, recreation, and medical care.
When thinking about risk, it is most important to consider how a potential investment’s price may vary with your existing portfolio and with your other sources and uses of wealth. Some examples:
Homeowner’s insurance - this investment is as bad as a lottery ticket. Why would a risk averse homeowner choose an investment with a negative expected return? Because insurance reduces the uncertainty of his or her lifetime consumption. The probability that a disaster will destroy any specific policyholder’s house is tiny, but if it does, the loss to that homeowner can be catastrophic. Most homeowners are happy to pay the annual insurance premium to eliminate this potential hit to wealth and lifetime consumption.
Too many eggs - it is particularly risky to invest most of your savings in your employer’s stock, as the former employees of Enron might warn us. Enron was an energy and trading company based in Houston, Texas. After roughly a decade of phenomenal success, Enron filed for bankruptcy in 2001. Many employees had most if not all their retirement savings in Enron stock, so lost their job and retirement savings at the same time.
2. The average dollar invested holds the market
I use a top-down approach when designing my investment portfolio. I start with the fact all investors must collectively hold the global market portfolio of all stocks, bonds, and other financial assets. Simple arithmetic then says the average dollar invested holds the global market portfolio.
Someone clever may be able to determine my “ideal” portfolio, but I would not trust a precise analytical solution to a problem as complicated and poorly defined as this.
My pro rata slice of the global market portfolio would probably be a fine choice for my portfolio if my preferences and circumstances matched those of the global average investor. But they don’t.
For example, if you live in Australia, almost everything you buy is in Australian dollars, and you are treated better than foreign investors (e.g., franking credits), so it makes sense you overweight your portfolio to Australian investments versus the global portfolio.
Your age, risk aversion and other issues like transaction costs, environmental factors and tax considerations (like concessionally taxed superannuation structures) also influence your portfolio.
But always be mindful of how your portfolio compares to the global market portfolio and ensure there is robust thinking behind why you have deviated away.
3. Chance dominates realised returns
People seem hardwired to identify patterns, whether they are real or not. Who hasn’t seen a ship in the clouds or human figures in a dirty window?
Given the importance of financial markets and the human inclination to identify patterns, it is not surprising that researchers and investors have found patterns in asset prices and returns for centuries and continue to do so now. It is also not surprising that a nontrivial fraction of the patterns are false positives i.e., we think someone has a skill, but they do not.
We can split an asset’s return into its expected return, which is our best guess of what will happen based on all the information currently available, and its unexpected return, which is the surprise – the difference between what actually does happen and what was expected.
Over reasonable investment horizons – three, five, ten, even 20 years – realised returns are typically dominated by the unexpected component (like a pandemic, 9/11 or the Global Financial Crisis) and inferences from realised returns are often false positives.
The performance of FAANG stocks – Facebook, Amazon, Apple, Netflix, and Google – over the decade from 2012 to 2021 illustrates the importance of unexpected returns. The 2012-2021 average annual return on a value weighted portfolio of these five large stocks is 30.09% and the cumulative ten-year return is 1166%. Should we expect the portfolio to deliver 1166% over the next decade? No. Strong unexpected returns are a better explanation for the great return and, by definition, the expected value of future unexpected returns must be zero – just as it is for every other listed stock.
The FAANG portfolio’s return in 2020 was a remarkable 61.47%. The success of the five technology stocks in the first year of the pandemic makes sense. The companies were selling entertainment, social interaction, and home delivery to a world of people isolated in their houses. The huge increase in the demand for FAANG services could have only been anticipated by someone whose crystal ball forecast COVID-19 and its consequences. Those who use recent returns on the FAANG portfolio to predict its future returns will probably be disappointed.
The incentives to identify new patterns in stock returns or to improve existing patterns are strong: degrees are awarded, papers are published, tenure is granted, and new investment products are sold.
How can an investor tell whether the winning pattern is gold or pyrite? Start by considering the model that justifies the pattern. If there is none, presume you are looking at the winner of a massive, uninformed search. A winning pattern is more likely to persist if the model that predicts it is compelling. For example, a model motivated by greed, fear, and transaction costs has potential. A model that works only if all returns are first converted to Turkish lira does not. Finally, the credibility of both the model and the pattern are enhanced a lot if the model obviously came first.
4. Active investing (i.e., stock picking) is a negative sum game
Dick Roll is a friend, finance professor, and pilot who flies his own plane. Many years ago I asked him whether his hobby was risky. He said the data imply it’s about as dangerous as driving a motorcycle. Dick is a smart and careful man, so I suggested the averages overstate the risk when he flies. His response changed the way I see the world: “Ken, every pilot thinks he’s better than average.”
Bill Sharpe published a great paper in the Financial Analysts Journal in 1991 that implies Dick’s insight about overconfidence extends to active investors (i.e., those who think they can pick the next winning stock). Sharpe’s paper, “The arithmetic of active management,” makes a simple point. The average dollar invested actively loses to a passive investment in the value-weighted market portfolio.
Sharpe’s argument is straightforward. Suppose I hold a passive value-weighted market portfolio, that is, I hold my pro rata slice of all stocks, bonds, and other financial assets in the global market portfolio. Since I hold the market, my return is the return on the market minus the low costs of maintaining my buy-and-hold portfolio. And since I hold the market portfolio, the combination of all other investors – passive and active – must also hold the market, and their combined return is the return on the market minus their higher costs.
Why are their costs higher? Because the active investors in the group pay extra management fees, transaction costs, and the other expenses of investing actively.
When choosing my own investments, I remind myself that most overconfident investors don’t realise they are, and that client fees pay for most investment managers’ yachts.
If active investing is a negative sum game, why does it persist? The most likely explanation is investor overconfidence combined with the fog of volatility. Given the high volatility of unexpected equity returns, active strategies and managers typically produce almost as many good monthly or annual returns as bad ones, which allows investor overconfidence to persist. There has been a gradual shift from active to passive since at least 1980, but as the meme stock events of 2021 remind us, seemingly uninformed and overconfident new investors enter the market every day.
Most investors also seem overconfident about their ability to evaluate managers. Suppose that after fees and expenses, the expected outperformance or alpha of the world’s greatest hedge fund manager is 5% per year. If her fund has equity-like volatility of 20% per year, how long should we expect to wait before confidently inferring (with a t-statistic of 2.0 or greater - which means we have confidence the data is meaningful) that her alpha is positive?
The answer is 64 years.
(In other words, to be certain this hedge fund manager can deliver a positive return over the market return, we need the fund to provide 64 years of performance returns!)
Why does it take so long to evaluate the manager? First, the highly volatile unexpected returns that let many underperforming active investors believe they are beating the market also obscure the great hedge fund manager’s skill. Second, hedge funds rarely track benchmarks and without a benchmark, 100% of the unexpected return is noise.
Index funds are easier to evaluate because each fund’s target index is a perfect benchmark, providing direct evidence of whether the fund is delivering as promised. Active equity funds are typically easier than hedge funds to evaluate and harder than index funds. Although a benchmark or asset pricing model may eliminate some noise, it can still take decades to decide whether an active fund’s under- or overperformance is the result of luck, skill, or a failed model.
Investor overconfidence about what one can learn from prior hedge fund or managed fund returns causes returns chasing, with new money flowing in after a relatively short period of good returns and flowing out after a similar period of poor returns. Some institutional investors have their own version of returns chasing, using only three to five years of returns to assess an active manager’s performance, with unlucky managers fired if the next few years’ returns are not better. The resulting portfolio churn is driven more by random unexpected returns than by meaningful information.
5. Most investors should diversify their portfolios
Warren Buffett and his partner, Charlie Munger, argue that academics are wrong when they advise investors to diversify. I think their argument reflects Buffett and Munger’s innate humility. If I had their abilities and circumstances, I would probably diversify as little as they do. But that is a big “if”.
Buffett and Munger’s argument against diversification makes sense only if they believe most investors share their ability to identify investments with extraordinary expected returns. For the rest of us, diversification can be a powerful tool.
It is important to remember, however, that the goal is not to reduce the volatility of any particular investment. It is to reduce the uncertainty about lifetime consumption.
Whilst there can be practical challenges translating academic research to the ‘real world’, Ken’s work is reflected in the Investment Philosophy espoused by Lorica Partners, which you can download and read here: https://loricapartners.com.au/what-we-do/investing
Author: Rick Walker