hope over reality, so I invested in equity index funds rather than in actively managed funds. More recently, my ideas began to change, based on my research and the research of others, and I am now a strong believer in active management.
In July 2002 I began managing what has become AthenaInvest’s flagship concentrated stock portfolio, Athena Pure Valuation/Profitability, earning a nearly 25% compound annual return over a 12-year time period. During 2013, it produced a greater than 60% return. One needs to remain humble whenever reporting results like these, since, as 2002 Nobel laureate Daniel Kahneman of Princeton University reminds us, “reversion to the mean can be just around the corner.”
But I am encouraged that we are heading in the right direction in that our other portfolios, among them mutual fund allocation, equity dividend, ETF, hedge fund, and global tactical ETF, are all producing superior returns. Like Pure, each portfolio is based on harnessing behavioral factors that have been identified through careful research as measurable and persistent emotionally-driven price distortions.
We do not attempt to out-analyze or outsmart other professional investors by creating a superior information mosaic for the investments we make. Instead, we attempt to understand the emotional crowds that dominate market pricing and, in managing our portfolios, exercise the consistency and persistence necessary to earn superior returns. In short, we practice BPM.
At first I was rather surprised by my portfolio performance. But as I conducted additional research and carefully reviewed the finance literature, I found that building a successful portfolio is not uncommon within the industry and the way in which I had been managing Pure is very similar to the way others who are successful manage their portfolios. Thus over time my methodology became embedded in a broader research stream which I will report on in the remainder of this book. The rest of this chapter is devoted to the foundational concepts underlying BPM.
Evolving market paradigm
Equity market theory has passed through two distinctly different paradigms over the last 80 years and currently is experiencing the rise of a third. The first paradigm was launched in 1934 when Benjamin Graham and David Dodd of Columbia Business School published Security Analysis, the first systematic approach to analyzing and investing in stocks. Graham and Dodd (GD) argued that it was possible to build superior stock portfolios using careful fundamental analysis and a set of simple decision rules. These rules were based on behavioral price distortions as identified by fundamental analysis. The success of GD is all the more impressive as their book appeared in the depths of the Great Depression, when stocks were crashing and market volatility reached levels not seen before or since.
GD’s dominance lasted 40 years, until it was pushed aside in the mid-1970s by the ascendency of Modern Portfolio Theory. MPT accepted the fact that there were many emotional investors, but argued there existed enough rational investors to arbitrage away any resulting price distortions and therefore market prices were informationally efficient. A prediction of this theory was that it was not worth conducting a GD type of analysis, nor any analysis for that matter, and instead an investor should buy and hold an index portfolio.
MPT immediately ran into problems in the late 1970s when S. Basu of McMaster University published a study demonstrating that low PE stocks outperformed high PE stocks and Rolf Banz of Northwestern University published a study in the early 1980s demonstrating that small stocks outperformed large stocks. MPT had no answer for these anomalies and so in order to save the model the two anomalies were sucked in as return factors. Never mind that it was never determined whether these represented risk or opportunities and that recent studies show these two effects disappearing. It was better to have them inside the theory rather than outside challenging the theory’s credibility. It has been downhill ever since for MPT, with study after study uncovering one pricing anomaly after another.
As MPT was rising to prominence, a parallel research effort was studying how individuals actually made decisions. The conclusion of this behavioral science research stream was that emotions and heuristics dominate decision making. It is amazing how little rationality was uncovered in these studies!
Because of the many problems facing MPT and the growing awareness of provocative behavioral science results, we are witnessing the decline of MPT and the rise of behavioral finance. Among other things, this transition brings back Graham and Dodd as an important way to analyze the market’s faulty pricing mechanism.
Behavioral portfolio management
Behavioral Portfolio Management, henceforth referred to as BPM, is an approach to managing investment portfolios that assumes most investors make decisions based on emotions and shortcut heuristics. It posits that there are two categories of financial market participants: Emotional Crowds and Behavioral Data Investors.
Emotional Crowds are made up of those investors who base decisions on emotional and intuitive reactions to unfolding events and anecdotal evidence. Human evolution has hardwired us for the short run, loss aversion, and social validation, which are the underlying drivers of today’s Emotional Crowds. Emotional investors make their decisions based on what Daniel Kahneman refers to as System 1 thinking: automatic, loss avoiding, quick, with little or no effort and no sense of voluntary control. [1]
On the other hand, Behavioral Data Investors, henceforth referred to as BDIs, make their decisions using thorough and extensive analysis of available data in order to tease out stable pricing relationships. BDIs make decisions based on what Kahneman refers to as System 2 thinking: effortful, high concentration, and complex. BPM is built on the dynamic interplay between these two investor groups.
MPT, as the prevailing theory of financial markets, posits that even though there are numerous irrational investors (think emotional, heuristic investors), the price discovery process is dominated by rational investors who quickly arbitrage away any price distortions. This implies a number of things regarding markets, such as prices fully reflecting all relevant information, the lack of excess returns to active investing, and the superiority of indexed portfolios over their actively-managed counterparts. In short, MPT contends that rational investors dominate the financial pricing process.
What if it is the other way around, that is, what if emotional investors dominate? Put another way, what if emotion trumps arbitrage? If this were the case, then price distortions would be common and could be used to build superior portfolios relative to the corresponding indexed portfolios. Active management could generate superior returns. In fact we would see the impact of emotions in every corner of the market and they would have to be taken into account when managing investment portfolios.
There is now ample evidence, which I will review shortly, supporting the argument that Emotional Crowds dominate market pricing and volatility. Emotional Crowds drive prices based on the latest pessimistic or optimistic scenarios. Amplifying these price movements is a market in which trading is virtually free and so there is little natural resistance to stocks moving dramatically in one direction or the other. “If anything is worth doing, it is worth overdoing,” is the market’s mantra.
Rational investors, or what I call BDIs, react to the resulting distortions by taking positions opposite the Emotional Crowd. But they are not of sufficient heft to keep prices in line. As a consequence, the resulting distortions are measurable and persistent. BDIs are able to build portfolios that harness these distortions as they are eventually corrected by the market, either rationally or simply because the Crowd is now moving in the other direction.
The Emotional Crowd, BDI interplay
BPM is built on the dynamic interplay between Crowds and BDIs. Crowds more often than not dominate market pricing and it is only by chance that individual security prices fairly reflect
