The Case for Growth
Theoretical and empirical work in finance over the past 50 years has led to an evolution in our understanding of how financial markets work. For instance, 40 years ago, building on the work of Harry Markowitz on portfolio selection and the efficient diversification of investments, William Sharpe and others initially thought there was only one dimension of expected returns in equity markets—the market itself.
In a highly influential paper published in 1992, Eugene Fama and Kenneth French synthesized much of the previous empirical research and showed that, controlling for market capitalization, companies with a low relative price (i.e., a high relative book-to-market ratio) have historically had higher average returns than companies with a high relative price. And controlling for relative price, small capitalization companies have historically had higher average returns than large capitalization companies.
Those results led Fama and French to conclude that there were at least two additional dimensions of expected returns in equity markets: one related to market capitalization or company size and the other related to relative price, as measured, for instance, by the ratio of book-to-market equity. Thus, Fama and French proposed a multifactor model to explain the average returns of stocks: the Fama/French three-factor model. According to that model, the expected return of an asset in excess of a risk-free rate is a function of that asset’s sensitivity to three common risk factors:
(1) A market factor, as measured by the excess returns of a broad equity market portfolio over a risk-free rate (in the case of the US, the 30-day US Treasury bill is usually considered the risk-free asset).
(2) A market capitalization (or size) factor, as measured by the return difference between a portfolio of small capitalization stocks and a portfolio of large capitalization stocks.
(3) A relative price (or value) factor, as measured by the return difference between a portfolio of value stocks or stocks with high financial ratios (high book-to-market stocks, in our case) and a portfolio of growth stocks or stocks with low financial ratios (low book-to-market stocks).
More recent research by Fama, French (2006), and Robert Novy-Marx (2012), among others, shows that expected profitability— as measured by the direct profitability of book equity, for instance—is another reliable and robust dimension of expected returns.
The market cap and relative book-to-market Fama/French dimensions of return are price-based. In the words of Joseph Chi and Jed Fogdall (DFA), the market forms the price to achieve a desired expected return. To transform price to expected return, it is necessary to take into account the expected cash flows to investors. The profitability dimension provides a way to discern expected returns of companies with similar price-driven characteristics; if two companies trade at the same relative price, the one with higher profitability will have a higher expected return, all other things being equal, than the less profitable firm. Chi and Fogdall emphasize that the research breakthrough in this case is not the discovery of expected profitability as a dimension of expected returns per se, but rather, it is the discovery of reasonable proxies for expected profitability, which allows the use of profitability as another dimension of expected returns in the creation of investment solutions.
In short, here are the main lessons of the theoretical and empirical research conducted over the past few decades:
(1) There are multiple dimensions of expected returns, and, therefore, multifactor asset pricing models are needed to explain differences in the cross-section of average returns.
(2) Four factors—the market, size, relative price, and expected profitability—capture much of the common variation in average stock returns in a way that is consistent with multifactor asset pricing models.
For any given portfolio, the higher the exposure to these factors, the higher the expected returns, all other things being equal. Thus, portfolios can be structured and managed to obtain the desired exposure to those dimensions (and capture the expected premiums associated with them), resulting in a portfolio with a higher expected return than the market.
A common way to assess the level of the expected premiums is to look at historical data and compute how those premiums have performed in the past. From 1927 to 2011 the US equity premium had an annual average of 7.94%. From 1927 to 2011, the US small cap premium had an annual average of 3.66%. From 1927 to 2011, the US relative price premium had an annual average of 4.73%. From 1975 to 2011, the annualized US profitability premium was 4.68% on average.
Profitability represents the other side of value. Strategies based on profitability generate value like average returns even though they are growth strategies. Because the excess returns from profitability strategies and value strategies are negatively correlated the two strategies work well together. In fact, a value investor can capture the profitability premium without taking on any additional risk. Adding a profitability (growth) strategy on top of an existing value strategy can actually reduce portfolio volatility.
Research also shows that actual returns related to the expected premiums are largely unpredictable, both in terms of when any dimension might outperform and which individual stocks will drive the performance. For these reasons, investors are better off structuring their portfolios along the different dimensions of expected returns, and continuously targeting these dimensions with broadly diversified, passively designed and efficiently structured portfolios. This approach maximizes the likelihood of capturing the expected premium associated with each dimension of returns.
Eugene F. Fama and Kenneth R. French, “Profitability, Investment, and Average Returns,” Journal of Financial Economics 82 (2006):
Robert Novy-Marx. “The Other Side of Value: The Gross Profitability Premium June, 2012 Simon Graduate School of Business, University of Rochester, Rochester, NY
Joseph Chi and Jed Fogdall, "Integrated Equity Solutions" Dec 2012. DFA Institutional Quarterly Review