A comprehensive manager due diligence process can be summarized via a simple heuristic we will refer to as the five Ps – performance, people, philosophy, process and portfolio. All of these individual components of the due diligence framework are important of their own accord, but they are also linked to each other in a feedback loop creating a virtuous (or vicious, as the case may be) self-reinforcing cycle. A talented investment team is more likely to implement a successful culture and investment strategy, which is more likely to lead to an effective investment process that generates a solid portfolio yielding strong performance. Such success leads to confidence, reaffirming the philosophy and reinforcing the focus on performance and the drive to succeed, and the cycle repeats itself. A crack anywhere in this chain can potentially cause the cycle to break down, and reduce the likelihood for persistence of desired returns.
The Five P's of Due Diligence
At each node in this framework, it is important to note that there is no need to arbitrarily distinguish between business questions or investment questions. Instead, the focus of the researcher should be on the substance of that nodule, attempting to arrive at a thorough understanding of all the elements that have led to, and subsequently resulted from, that particular “P”. The question: “What has their performance been and how was it generated?” not only leads to questions about historical market conditions and past portfolio exposures, but also about the people and processes that were responsible for those prior results. It is only by fully understanding these five Ps – both in the past and the present – that a researcher can set reasonable expectations for the future.
Performance (or performance, performance, performance!)
The manager selection process quite literally begins and ends with performance. As with all of the five Ps, on a stand-alone basis the presence of attractive historical returns may be viewed as a necessary but not sufficient condition in order to consider an investment with a manager. While the mantra of “past performance is no guarantee of future results” is repeatedly (and rightfully!) ingrained in all investment professionals, it may be easier to set realistic expectations about the future performance of an investment manager in the less benchmark-constrained realm of alternatives after reviewing some amount of historical data, be that the previous returns of the fund, a managed account composite or even just a track record at a prior firm. At the very least, after initially reviewing the historical performance, it may become obvious in some instances that the strategy is incompatible with the desired return profile for that specific investment, and due diligence can be discontinued.
While some investors may make manager-hiring decisions with little to no historical evidence of performance, the larger percentage of institutional allocators do indeed require at least some track record to evaluate. In fact, many institutions have a minimum requirement, such as a three-year track record, before they will even consider an allocation. Such a requirement is certainly arbitrary, and frankly is as much a heuristic intended to make the institution’s opportunity set more manageable as it is an intentional tilt in the due diligence process. In a research piece titled “Solutions to Accessing the Public Equity Markets: Structured and Active Strategies,”consultant Fund Evaluation Group (2013) supports the argument that there might be a valid reason for such a requirement when evaluating active strategies.
It is possible to search for statistical evidence of investment skill, or alpha, in the historical performance of a manager. Doing so at a certain confidence level requires a minimum sample size of observations. The sample size required is related to three factors: the amount of alpha or out-performance relative to the benchmark, the amount of tracking error or noise around that benchmark and the confidence level. The Fund Evaluation Group (2013) demonstrated that two to four years is an appropriate sample size if managers generate alpha of 3–5% with tracking error of 2–4% at the 95% confidence level. Certainly, a three-year track is no guarantee of future results, but as Table 15.1 suggests, it may in fact provide some relevant information for performance analysis.
Readers might note that such short track records are only statistically relevant if there exists fairly high levels of alpha to begin with, to which I would counter that perfectly rational investment decisions may not require a 95% level of certainty; would anyone pass up a 75% edge in a game of chance?
Since it is not practical to restate all the research that has been conducted on excess returns or persistence of performance, I will summarize. Mutual fund managers on average generate negative alpha and demonstrate virtually no persistence of performance. On the other hand, both hedge funds and private equity funds may generate alpha on average, and do so persistently, although they may not. And even if they have in the past, it is certainly less so today. However, it does appear that the higher dispersion of returns in alternatives compared to traditional investment strategies, results in stronger performance for those managers in the top quartiles. Maybe.
It is also plausible that true alpha does not exist at all, or is so rare as to suggest it is a fool’s errand to try to identify it ex ante. It is worth noting here that alpha is generated in real time. Often, research identifies betas ex post that were responsible for the return stream, but if those betas were not previously available in any low-cost, easily accessible solution, then they may not have truly been betas at that time. Perhaps, then, true alpha rests in a manager’s ability to identify the next as-of-yet undiscovered beta.
All of these arguments have their proponents, both in academia and the practitioner community, and a great deal of intellectual capital has been spent in this semantic debate. However, at the end of the analysis, it may not matter. Rather than approaching manager selection purely as a search for alpha generators, it might be more effective to display a bit of humility in acquiescing that alpha is hard to find – and, if you do find it, you might have very well simply misidentified some beta(s). Such an approach accedes to the commonly employed methods of evaluating individual manager performance, but also concedes that these methods are imperfect and their results should be taken with a grain of salt.
The ability to hold contradictory hypothesis simultaneously may be an advantage in conducting performance analysis. Alpha exists, but it is extremely rare. It is difficult to find, but investors still try. When someone does find it, it is most likely luck or a mis-specified beta. Acknowledging that the “alpha” game may well be an exercise in futility allows manager researchers to simultaneously search for managers that also access betas and replicable investment processes that generate attractive risk-adjusted and stand-alone returns, in addition to the (potentially futile) search for alpha. I recommend a three-pronged approach to evaluating historical returns: attempting to find managers that have demonstrated evidence of generating acceptable returns across multiple measures of alpha, as well as traditional risk-adjusted return such as the Sharpe ratio and also simple total return. After all, you do not eat the Sharpe ratio, and you also do not eat alpha. You eat total return. Managers that can generate desirable performance on all measures may be less likely to disappoint in future periods.
I would propose we search for a more generalized form of investment skill. The search for alpha is really the search for managers with a steeper learning curve than other managers, or perhaps the ability to find attractive betas or market exposures that are not yet widely accessed by other market participants or appreciated by the broader financial academic community.
This then focuses the discussion around the second “P”: people. In analyzing the people responsible for creating the performance, the due diligence professional should search for the presence of characteristics shown to be associated with cognitive skills and learning ability. The presence of these traits may increase (decrease) the probability that the attractive performance results were likely attributable to skill (luck), and thus may increase the probability of the continuation of desirable performance in future periods.
Readers should note a final word of caution on performance analysis. Humans, despite our best efforts at rationality, suffer from several well-documented biases in decision-making. During the discussion on the five Ps, I will endeavor to address some of the most significant biases as they relate to each section. The obvious goal of this is the hope that awareness of these mental heuristics can support a conscious effort to counteract their effects.
Any attempt to find investment managers who have generated superior returns in the past is very likely subject to the “recency effect” or, as it is more commonly known in investing, “performance chasing”. Simply put, the recency effect is the tendency for people to place undue weight on recent events or data points. The result of this bias in an investment context is that investors, both individual and institutional, tend to believe that the future will look to a great extent like the immediate past. Therefore, they have a tendency to buy stocks that have recently gone up and naively hire managers that have dramatically outperformed.
Therefore, although due diligence begins and ends with performance, it is important to ensure the due diligence professional is vigilant against biases, and approaches the analysis with a healthy dose of humility to avoid – to the greatest extent possible – naive performance chasing.
Next, I'll discuss our framework for assessing People.
