Are you ready for your second graduate level discussion on investing, and how to build a portfolio? We’ll again promise to keep the jargon to a minimum, and to explain academic terms, if we can’t avoid using them.
At Springwater, our approach to building investment portfolios for our clients is based on decades of academic research. That research explains how securities like stocks (and bonds, and mutual funds) are priced. It also provides a blueprint for how to build portfolios with the best risk and return characteristics.
We previously looked at asset pricing. Let’s now consider portfolio construction.
The Fama French Three Factor Model is an asset pricing model that expands on the Capital Asset Pricing Model, which we introduced previously.
Professors Eugene Fama and Ken French were professors at the University of Chicago business school, and in the early 1990s began researching ways to better measure stock market returns.
Their research showed that, over time, small company stocks (as measured by their market value) tend to outperform those of large companies, and value stocks tend to outperform growth stocks. In fact, Fama and French found that when size and price (or value) factors are combined with the beta (or market) factor, they could then (statistically) explain as much as 95% of the return in a diversified stock portfolio.
So, the three factors in the Fama French model are defined as (1) the market; (2) size, and (3) price, or value.
Let’s look in a bit more detail at each of the three factors.
The market factor simply indicates that over time, a diversified portfolio with a higher allocation to stocks will outperform a diversified portfolio with a lower allocation to stocks. In the short term, of course, “all bets are off”, but over long periods of time, a portfolio allocated, say, 60% to stocks can be expected to generate a higher return than one allocated, say, only 40% to stocks.
The size factor indicates that, to the extent that two diversified portfolios have the same allocation to stocks, the portfolio with a “tilt” to – or greater weighting in – small company stocks (versus large company stocks) can be expected, over time, to generate higher returns. Investors can readily obtain information about a company’s market capitalization (defined as the total market value of a company).
The price factor indicates that, to the extent that two diversified portfolios have the same allocation to stocks, the portfolio with a “tilt” to – or greater weighting in – value stocks (versus growth stocks) can be expected, over time, to generate higher returns. Value stocks are commonly defined as those whose price is (hopefully temporarily) depressed, relative to some fundamental measure, like the company’s cashflow, dividends, earnings or sales.
The size factor makes sense to most investors. It seems intuitive that investing in a small company is inherently riskier than investing in a large one, and thus that investors would demand a higher expected return for doing so. The little coffee shop down the street is a riskier investment than, say, Microsoft or Apple, and so an investor in the former would expect a correspondingly higher return.
The price factor is less intuitive, but an example may help. Consider a company facing one or more business challenges – these could be market-related, internal, regulatory, etc. Given an assumed figure for next year’s sales, cashflow, dividends, etc (the fundamental measure we referred to earlier), the company’s stock price will begin to fall, because investors are skeptical about the company’s ability to meet the challenge(s). At a certain point, though the stock price will have fallen so far that some investors will be willing to take a chance on the company and its ability to recover. If it does, the stock price will rebound and the investors will be rewarded for the risk they took.
So, now let’s imagine a conversation over drinks between two investors, Tim and Jerry, who are comparing the returns on their portfolios over the past decade. Jerry asks Tim how his portfolio has performed, on average, and Tim answers, “I’ve earned about 8% per year”. Jerry is surprised, because his portfolio has earned less than 6% over the same time period. Both men work with a competent investment advisor, and thus have well-diversified portfolios. Given that, it’s probably safe to guess that Tim had a higher allocation to stocks, while Jerry probably had more invested in safe, lower-return bonds and cash. And, in fact, Jerry confirms this to Tim – he’s allocated only 50% of his portfolio to stocks, while Tim has had 75% of his portfolio invested in the stock market.
But let’s say that Tim and Jerry coincidentally find that they had an equivalent exposure to the stock market of, say 60%. Well, then it’s probably safe to guess that Tim (who earned an 8% average annual return) had included more small cap and/or value stocks in his mix, compared to Jerry (who earned a 6% average annual return).
One significant caveat to the Fama French research is that long time series of data are needed for these factors to hold true. In other words, there can be long periods where “growth” outperforms “value” (see 2009-2019), “large cap” outperforms “small cap” (see the 1990s), or even when bonds and cash outperform stocks.
Finally, there is debate amongst academics and investors about whether the outperformance by small cap and value stocks is due to market efficiency or market inefficiency. Those who attribute the outperformance to market efficiency argue that the difference in returns is generally explained by the excess risk that value and small cap stocks face as a result of their higher cost of capital and greater business risk. In contrast, those who attribute the outperformance to market inefficiency believe the outperformance is explained by investors incorrectly pricing the value of these companies, which provides the additional return in the long run, as the stock value adjusts.
The Fama French Three Factor Model is one of the foundations of modern investment theory. The now-familiar Morningstar nine-box style chart is a direct result of the work by Fama and French. In 2013, Professor Fama received the Nobel Prize in Economic Sciences for “empirical analysis of asset prices”.
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