Where Do Returns Come From?

You don’t need a lot of mathematical horsepower to be a Couch Potato investor. Indeed, simplicity is one of the strategy’s virtues: just keep your costs low, diversify widely, and stick to the plan. But if you’re a finance geek, it can be fun to delve into the more arcane theories behind index investing.

One of the most interesting chapters in Rick Ferri’s The Power of Passive Investing (Wiley, 2010) looks at how academics have learned where investment returns come from. Twenty years ago, if a money manager beat the market, it was pretty much impossible to explain why. Was the outperformance due to skill (or alpha)? Did the manager simply take more risk? Or did he just get lucky? Until recently, we didn’t have the tools to answer those questions.

Now we can get very close. The work of professors Eugene Fama and Kenneth French in the 1990s showed that a portfolio’s returns can be largely explained by three risk factors: its overall allocation to stocks (called the market factor, or beta), its exposure to small-cap stocks (the size factor), and its exposure to stocks with high book-to-market ratios (the value factor). In plain English, this means stocks are riskier than fixed-income investments, and therefore deliver higher long-term returns. In addition, small-cap and value stocks are riskier than the overall market, and therefore also have higher expected returns.

This is now known as the Fama-French Three Factor Model, and it’s the basis of the equity strategy used by Dimensional Fund Advisors, who offer the most sophisticated passively managed mutual funds around. (It’s also the basis of my Über-Tuber ETF portfolio.)

The power of three

All of this might seem obvious today. The idea of beta (the first of the three factors) has been around since the 1960s, and the first studies showing that small-cap stocks outperform large caps appeared in the early 1980s. Value investing is an even older idea. “People have known that value stocks outperform since the beginning of the last century,” Ferri explained in our recent interview. Benjamin Graham and David Dodd published Security Analysis in 1934, and the book is still widely read today. Less well known is John Burr Williams’ The Theory of Investment Value, published in 1938. “Williams talked about how important dividends are. From the 1880s through to the 1950s, stocks typically paid over 60% of their earnings in dividends. So the book was basically about how investment value is based on dividends, which is a value-type factor.”

The problem with these early investing theories was that it was that they couldn’t be quantified. Before computers and databases of historical returns, it was impossible to tease out these factors and use them to explain a portfolio’s performance. There were also different ideas of what a value stock was. Did that mean one with a high dividend yield? A low price-to-earnings multiple? A high book-to-market ratio?

The analysis began in the 1970s, Ferri explains, “but it was Fama and French who really quantified everything and put it all together. They were able to create a simple, elegant model of why portfolios perform the way they do.” This elegant model demonstrated that a money manager’s supposed skill could be an illusion. A fund’s outperformance may not be due to alpha at all; it might simply be the result of the fund’s exposure to the Fama-French factors.

Think of it like this: no one celebrates an equity fund manager who outperforms a bond fund, because it doesn’t take skill to simply accept stock market risk. Fama and French took this idea two steps further. Say, for example, a Canadian equity fund beats the S&P/TSX Composite Index over some period, and the manager takes credit for her superior stock-picking skills. An analysis using the Fama-French model can reveal whether the fund had more exposure to small and value stocks compared to the overall market. If it did, then the manager did not add any alpha. Investors in the fund were simply compensated for taking more risk.

No need to pick stocks

Ferri elaborated on this idea in our chat. “What this means is that you can analyze the monthly returns of any broadly diversified stock portfolio over a 10-year period, and without knowing anything else, you can determine what percentage was in value stocks, and what percentage was in small-cap stocks. Then when you actually look at that the portfolio to see what stocks were in it, lo and behold, that’s the way it was invested. The model is rigorous, and it’s statistically significant.” Fama and French found that beta alone explained about 70% of returns, while the size and value factors accounted for another 25%.

The upshot was that now you didn’t need a brilliant manager to pick individual stocks: you could simply design a portfolio that was exposed to the Fama-French risk factors in whatever proportion suited your goals. “Now we have a new model for building portfolios, and you can use passive funds to do it. You don’t need security selection: you’re going to get 95% of the way there with index funds. And the lower cost of doing it this way overrides any benefit that you might get from individual security selection.”

So if your investment strategy is based on picking individual securities, or on hiring professional managers to do that for you, the Fama-French research suggests that these decisions will impact a mere 5% of your portfolio’s overall performance. Even then, chances are that the impact will be negative.

For readers who want to learn more, I’m giving away a copy of Rick Ferri’s The Power of Passive Investing. Just leave a comment below or Tweet this post before midnight on Sunday, March 27, to enter the draw.