The TEXPERS Blog

Assessing the Merits of 

long-only equity allocations

By Marlena Lee, guest columnist

Investors continue to search for effective ways to structure their long-only equity allocations.

Many passive approaches have offered diversified exposure at low management fees with a minimal governance burden. However, concerns about the potential for a sustained period of lower returns have prompted some investors to revisit their decision to index and contemplate adding factors to their portfolios. Assessing the merits (and limitations) of any “factor-based” approach requires asking some seemingly fundamental but important questions:

• Why should there be differences in expected returns across stocks? The chance that all stocks have the exact same expected return is virtually zero. There is a multitude of reasons why different stocks should have different expected returns, such as differences in risk or differences in investor preferences.
• How can you identify these differences in expected returns? A good rule is that investors should not rely solely on back-tested results. There is a saying in statistics – if you torture the data long enough, it will confess to anything. A sound theoretical and empirical framework reduces the chance that a coincidental pattern in historical stock data will affect our conclusions.Valuation theory suggests the price of a stock depends on a few variables. One is what the company owns minus what it owes (book value). Another is what investors expect to receive from holding the stock (expected profits) and the discount rate they apply to those expectations (the investor’s expected return). This framework provides very useful insights. One insight is that the expected return investors demand for holding a stock drives its price. Another is that combining price with book value and expected profits allows us to identify differences in expected returns across stocks. For a given level of expected future profits, the lower the price, the higher the discount rate. For a given price, the higher the expected future profits, the higher the discount rate. Empirical analysis is also important – it can help inform expectations about the magnitude of premiums and build confidence that the premiums we see in the historical data are not there by chance. There are numerous studies documenting size, value, and profitability premiums using many different empirical techniques on large data sets—90 years of US data, 40 years of non-US developed markets data, and 30 years of emerging markets data. If we can expect premiums and have a good way of identifying them, we still need to assess how best to capture them.
• How confident are you that premiums can be captured? What are the risks? If the premiums can be pursued in a well-diversified strategy, this improves the likelihood they can be captured by investors. Why? If results are driven by a small group of stocks or a small percentage of market cap, it is more likely to be a chance result. Additionally, less diversified strategies pursuing premiums are likely to have higher turnover and higher costs.  

Our experience is that using current market prices is important in identifying and capturing premiums. Combining current prices with company fundamentals creates an instantaneous snapshot of differences in expected returns. At that specific instance in time, stocks with lower relative prices and/or higher profitability have higher expected returns. If there is a spread in relative prices at any point in time, we should expect a value premium. This implies we can use current prices to continually focus on higher expected returns.

This does not mean that higher expected returns will be realized continuously, or even consistently.  For example, it is not unprecedented to see value stocks trail growth stocks over a 10-year period. A period of underperformance like this, however, is not by itself compelling evidence that one should no longer expect a value premium in the future. While there is a non-zero probability that any realized premium can be negative over any given investment horizon, that probability decreases over longer investment horizons.

While we encourage a long-term focus, we acknowledge that doesn’t make any underperformance over the short term less disappointing. Asset owners must be willing to accept that uncertainty as part of investing in premiums, just as they do investing in equities. Asset managers can help by not adding to that uncertainty through chasing chance results or inefficiently targeting premiums.

We believe a strong partnership with clearly set expectations, a long-term focus and expertise in implementation can translate to better outcomes for intermediaries and, ultimately, plan participants.

Dimensional Fund Advisors LP, an investment advisor registered with the Securities and Exchange Commission, receives fees for investment management services provided to client members of TEXPERS. There is no guarantee of strategy success. This information should not be construed as investment advice.

About the Author

Marlena Lee

Marlena Lee is co-head of research and vice president at Dimensional Fund Advisors in Austin. As co-head of research, Lee helps manage the firm's general research efforts. She shapes the research agenda by working with clients and the Sales and Investment teams to identify research topics on a variety of investment-related matters that may be useful to clients, including asset pricing, asset allocation, and retirement. Lee is also a member of the Investment Research Committee. Prior to joining Dimensional, she worked as a teaching assistant for Nobel laureate Eugene Fama, a professor at the University of Chicago Booth School of Business. Lee earned her doctorate in finance and a master's degree from the Chicago Booth School of Business. She also holds a Master of Science in agricultural and resource economics and a Bachelor of Science in managerial economics from the University of California, Davis.