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Two weeks ago, I introduced the concept of behavioral portfolio management (BPM) as a way to build superior portfolios.
Last week, I discussed the first basic principle underlying BPM: Emotional crowds dominate market pricing and volatility. In this article, the third in a series of five, I will discuss the second basic principle.
What is BPM?
BPM posits that there are two categories of financial market participants: emotional crowds and behavioral-data investors (BDIs). Emotional crowds are made up of investors who base decisions on anecdotal evidence and emotional reactions to unfolding events. Human evolution hardwires us for short-term loss aversion and social validation, which are the underlying drivers of today’s emotional crowds. On the other hand, BDIs thoroughly and extensively analyze behaviorally driven price distortions and build portfolios based on these distortions.
Basic principle II: Behavioral-data investors earn superior returns
Emotional crowds dominate pricing; that was the first basic principle, which I demonstrated last week. This would seem to indicate that BDIs earn superior returns by taking positions opposite the crowds. But this is not necessarily the case. Though there is little doubt emotions increase volatility, the resulting distortions might be random and unpredictable, making it difficult, if not impossible, to take advantage of them. So beyond proving the fact that emotions drive prices, it is necessary to show that the resulting distortions are measurable and persistent.
The behavioral finance literature is full of examples of measurable stock price distortions.1 It would seem easy to build superior performing portfolios, but doing so would mean taking positions that are opposite the crowd. The powerful need for social validation acts as a strong deterrent for many investors, discouraging them from pursuing such an approach. It is tough to leave the emotional crowd and become a BDI. Thus, though we find price distortions to be measurable and persistent, building a portfolio benefiting from them is emotionally challenging.
In order to demonstrate that it is possible to earn superior returns, I turn to the active equity mutual fund research. This group of investors is one of the most studied in finance because of the availability of extensive data over long time periods. One stream within this large body of research reveals that active equity funds are managed by successful stock pickers.
2 These studies examined individual fund characteristics and holdings and confirmed that a significant number of funds outperformed, as did their top stock picks.
The most compelling results were reported by Cohen, Polk and Silli (CPS, 2010), which are reproduced in Figure 1. This graph reveals that a fund’s best idea stock, as measured by the largest relative portfolio weight, generated an average risk-adjusted after-the-fact alpha of 6%. What is more, the next best idea stocks also generated positive alphas. This demonstrates that it is possible to build a superior stock portfolio.
The study did not explore the source of these returns, but it is reasonable to conjecture that much of the return is the result of BDIs (i.e., buy-side analysts and portfolio managers) taking positions opposite the crowd. This conjecture could indicate that the investment team’s ability to accumulate superior information about the stocks in which they invest is less important. It is difficult to untangle these two return drivers. For now, we are left with the plausible supposition that emotionally driven prices are the most important source of excess returns for fund managers.
Based on Graph 3 in Cohen, Polk and Silli (2010). The graph shows, over the subsequent quarter, the average six-factor adjusted annual alpha for the largest relative overweighted stock in a mutual fund portfolio, the next most overweighted and so forth. Based on all active U.S. equity mutual funds 1991-2005.
Reconciling two stock-picking skill research streams
A better known conclusion from this line of research is that the average active equity mutual fund earns a return that is less than or, at best, equal to the index return.3 That is, the average fund earns a zero or negative alpha. This leads to the oft-stated conclusion that equity fund managers lack stock-picking skill, just the opposite of the conjecture I presented above.
One would think that professional investors, such as mutual funds, hedge funds and institutional managers, would be BDIs. And indeed, the analysts within such organizations are most often BDIs. But the further up one goes in the organization and the larger the fund, the more like the crowd it becomes.
In order to grow assets under management, funds must attract and retain emotional investors, which means catering to client emotions and taking on the features of the crowd. As the fund grows in size, it increasingly invests in those stocks favored by the crowd, since it is easier to attract and retain clients by investing in stocks to which clients are emotionally attached. A fund might also mimic the index to lock in a past alpha or become a closet indexer to avoid style drift and tracking error. Each of these represents a different way of catering to investor emotions.
So, what may start out as a fund managed by BDIs taking positions opposite the crowd often ends up morphing into something that is acceptable to the crowd. As argued by Berk and Green (2004), such behavior is rational on the part of the fund, as revenues are based on assets under management. Consistent with this argument, others have found that returns decline as funds grows large.4
Conclusion
Ample evidence supports the argument that emotional crowds dominate market pricing and volatility – the first basic principle. Emotional crowds drive prices based on the latest pessimistic or optimistic scenarios. Because stock trading is virtually free, there is little natural resistance to stocks moving dramatically in one direction or another, amplifying price movements.
There are two sources of empirical support for the second basic principle, which is that BDIs can earn superior returns. First are the documented price distortions, and second are the excess returns earned by active equity mutual funds on their best-idea stocks. But many investors will find it more difficult to embrace the second principle than the first, since the emotional barrier of social validation must be overcome in order to build a successful BDI portfolio.
In the remaining two articles in this series, I will discuss how to build portfolios that take advantage of pricing distortions. As BDIs know, the market eventually corrects distortions, resulting in superior portfolio returns.
C. Thomas Howard is Professor Emeritus, Reiman School of Finance, Daniels College of Business, University of Denver and CEO and Director of Research, AthenaInvest, Inc.
Contact information: [email protected] (877) 430-5675 x100. A longer version of Behavioral Portfolio Management can be obtained at the Social Sciences Research Network website.
Read more articles by C. Thomas Howard, PhD
