Quarter 1, 2007

Overview: If you know baseball, you know Bill James. To most serious baseball fans, Bill James revolutionized how individuals use statistical research to analyze the game of baseball. Today, such statistical analysis, known as sabermetrics, is integral to the game. For fans who share a love of the game and a penchant for statistics, the research done by James has elevated the sport to another level - tying together baseball's past and present to create an all-encompassing numerical art form and a new way to view the game.

In much the same manner, professors Eugene F. Fama and Kenneth R. French have changed the field of financial economics. The findings from their groundbreaking research have changed how prudent individuals approach investing. Fama and French have a dedicated following in the academic community but the effects of their research transcends this group. This article discusses James, Fama and French and looks at how their work has enhanced their respective fields.

In 1977, Bill James' self-published the book, 1977 Baseball Abstract: Featuring 18 Categories of Statistical Information That You Just Can't Find Anywhere Else and sold just 75 copies.1 Today, James' annual edition (now called The Bill James Handbook) is considered a "must read" for all serious fans of our national pastime. How could James change baseball by analyzing statistics?

By conducting vigorous statistical research, James demonstrated that certain statistics were key to determining the effectiveness of a player. Among his many findings, was the realization that a player's batting average and the number of home runs hit were not as important as people had originally assumed. James found that other statistics, namely the total of a player's on-base percentage and his slugging average, were actually better indicators of a player's abilities.

What James did was nothing less than revolutionize the way that people think about baseball statistics and how to build a winning team. In fact, many major league baseball teams today employ statistical experts, called sabermaticians. Michael Lewis's best-selling book, MoneyBall, explains how Billy Beane, the general manager of the Oakland Athletics, used sabermaticians to build a winning team despite having a very limited payroll.2 With one of the lowest payrolls in baseball, the Oakland Athletics went to the playoffs from 2000-2003 and have won more than 90 games every season since 2000.

Just as James revolutionized the game of baseball by assessing which factors were the most important in determining the impact a player had on the outcome of a baseball game, professors Eugene F. Fama and Kenneth R. French continue to have a dramatic impact on the field of financial economics. In June 1992, their landmark paper, "The Cross-section of Expected Stock Returns," was published in the Journal of Finance. The Fama-French research produced the "Three Factor Model," which explains most of the variability in returns of diversified U.S. stock portfolios.

In addition, their research reveals that "active investing" - individual security selection and market timing - does not play a significant role in explaining equity returns, and thus should not be expected to add value. If using those techniques did explain returns, then we would see evidence that active managers are adding value, instead of subtracting it - which is what the academic evidence actually indicates.

Nevertheless, many investors continue to invest using active management strategies, although much of the research coming from the academic community, including that of Fama and French, has ruled out its effectiveness.

To draw a parallel to James' work, not everyone has jumped on the sabermetrics bandwagon. Many individuals who follow baseball (particularly the media that cover the sport) have been slow to accept the idea that there may be a better way to analyze the game. "Most writers continue to rely on outmoded measures like batting average even after their publications have given stellar reviews to a book that lays bare the inadequacies of such stats."3

One significant conclusion that can be drawn from the Fama-French research is that the markets are largely efficient. Therefore, the vast majority of the returns one can expect from a diversified equity portfolio are unrelated to the ability to pick stocks or to time the market. Instead, the degree of exposure to three risk factors determines the vast majority of variability in returns. Those factors can be defined as follows:

s        Equity versus Fixed Income - This factor refers to the amount of exposure your portfolio has to the overall stock market, as compared to how much fixed income it holds. Any portfolio with equities will have some exposure to this risk factor. Since equities are riskier than fixed income investments, they provide greater expected returns.

s        Equity Size - This factor refers to the size of a company as determined by market capitalization. We know that small companies are riskier than large companies, so they must provide greater expected returns.

s        Equity Value - This factor refers to a company's book-to-market (BtM) classification.4 As an example, the definition of a value stock used by the University of Chicago's Center for Research in Security Prices (CRSP) is consistent with Fama-French's work, in which stocks are ranked in one of 10 categories. Stocks ranked in deciles 1-3 by BtM are considered growth stocks, and those in deciles 8-10 are considered value stocks.  High BtM (value) stocks are riskier than low BtM (growth) stocks, so they must provide greater expected returns.

Because of their research, we have a similar two-factor model to explain the vast majority of returns of fixed income portfolios. The two risk factors are term and default (or credit risk). For term risk, the longer the bond's term to maturity, the greater the risk to investors who hold such bonds.  For default risk, the lower the bond's credit rating, the greater the risk to investors who hold such bonds. The markets also compensate fixed income investors for taking such risks with higher expected returns.

The consequences for baseball fans unaware of new statistical evidence may only be as harsh as being blindsided by a losing season. However, the implication for investors who understand the Fama-French research hits closer to home, namely meeting their investment objectives. If investors are aware that efforts to outperform the market by either security selection or timing are highly unlikely to prove productive (especially after the costs, including taxes), they can adjust their investment strategy accordingly. Thus, a prudent investment strategy should include the following:

s        Developing a portfolio that reflects your unique ability, willingness, and need to take risk. The equity portion should be globally diversified across multiple asset classes. The fixed income portion should be diversified in terms of credit and term risk, as appropriate.  

s        Using passively-managed funds that are both low-cost and tax-efficient. In the case of fixed income assets, those individuals who have sufficient assets to do so should consider building a portfolio of individual bonds.

s        Having the discipline to stay the course, ignoring the noise of the markets as well as the emotions that are caused by the noise. Those emotions can cause you to abandon even the most well developed plans.

Why are some individuals unable to make a change in the face of what we would consider convincing evidence? One explanation may be that, when someone is very familiar with a certain way of thinking - about investing or baseball - it is hard to make the leap to another model.

In late 2002, the Boston Red Sox hired James as a senior baseball operations advisor. In 2004, they won the World Series, breaking baseball's most famous curse. Fama and French continue to make significant contributions to the field of financial economics while teaching at the University of Chicago and Dartmouth College, respectively. Although the venues in which they operate are quite different, Fama, French and James have each made significant contributions to their respective industries that require participants to consider new alternatives and reject old beliefs. This is often not as easy as it appears, but in many cases, it is well worth the effort.

1        Michael Lewis, Moneyball: The Art of Winning an Unfair Game. W.W. Norton & Company, 2003.

2        Ibid.

3        Carl Bialik, In the Fray: Sabermetrics Goes Mainstream. Wall Street Journal, July 1, 2003.

4        Book-to-market (BtM) is a ratio of a firm's accounting value and market value. The higher the BTM, the less investors are paying to own a company when they purchase stock.