Identifying the factors most commonly associated with alpha generation and destruction by equity fund managers
By Chris Woodcock
It is well known that alpha — the measure of a portfolio manager’s success (or failure) in beating the performance of the broader market he or she invests in — is the holy grail of active portfolio management.
Managers who generate enough alpha to beat the returns of low-fee index funds by more than their own fees demonstrate that active fund management can — and does, in these circumstances — represent a better value than passive index investing.
But like the holy grail, alpha is elusive. It is difficult to generate in the first place, and even more challenging to reliably replicate. In fact, while it’s easy to measure a portfolio’s overall alpha, no one has systematically identified where in the manager’s decision-making process that alpha is actually originating.
The source of alpha — the single most important determinant of successful active portfolio management — has been shrouded in mystery.
The Essentia research team has concluded a three month examination of the origins of portfolio alpha — where in the myriad decisions made and actions taken by portfolio managers it tends to be generated or destroyed.
Our results were twofold. First, we found very few common sources of alpha across portfolios. With a handful of exceptions — which we’ll discuss below — most portfolios have their own unique fingerprint of what leads to the alpha they create (or lose).
Second, and most importantly: in 100% of the portfolios we studied, we identified at least one factor — or categorizer, in our terminology — that significantly impacted alpha, for better or for worse. This has profound implications for all active portfolio managers. Our work shows that it is possible for managers to identify where in their decision-making process they tend to create or destroy alpha — and once that is known, the door is open for them to expand or enhance what adds alpha, and correct what diminishes it.
Our study analyzed 60 portfolios over 14 years and identified distinct areas of manager decision-making directly tied to the alpha generated (or lost) within each portfolio. We tracked 24 categorizers – ranging from equity sector to holding period to decision day of the week — across six broad investment decision categories, or skills: stock picking, size adjusting, entry timing, exit timing, scaling in and scaling out.
Sources of alpha were found in varying degrees across six key investment skills among the portfolios we analyzed. This chart shows the percentage of the portfolios in our study that contained at least one significant factor within a given skill.
In all 60 portfolios we analyzed, we found at least one factor that was significantly associated with the generation of alpha. Very few of those were common across the portfolios, but we did find that for a majority of managers (63%), alpha was associated with at least one factor within stock picking, most notably:
- Conviction Level: A significant number of managers demonstrated skill in picking stocks where they had strong conviction: namely, those in their top quintile of positions by maximum money invested. By contrast, a significant number of managers showed negative skill in the middle quintile of positions on this metric. This reinforces what we see in managers every day: positions that are neither proactively large or small often lead to alpha destruction – it’s a common “alpha leak.” In our analysis, these lower-conviction stock picks tended to destroy alpha at an average rate of 2.1% per investment.
- Exit Price Momentum: For 37% of managers in our sample, exit price momentum was strongly correlated with stock picking alpha. On average, we found that exiting stocks into negative momentum (a falling price, for a long position, or a rising price, for a short position) destroyed 6.2% of alpha at the portfolio level, per investment. In contrast, stocks exited into positive momentum added 5.1% of alpha at the portfolio level before the manager closed the position. So these managers had a marked tendency to finish a profitable episode on a high note, and an unprofitable one on a low note.
- Open vs. Closed Positions: Portfolios often showed a stark difference between alpha generated by stock picking decisions in open positions vs closed ones: on average, we found that open positions were contributing 13% of alpha at the portfolio level at the time of the analysis — while closed positions had generated -4.7% of alpha. While more investigation is required to interpret this result, we find this particularly interesting in light of our work into the lifecycle of alpha: in some managers it may be evidence of the “round tripper” effect (in which managers hold their stocks too long and sell only after all alpha has been exhausted) we identified in that research. (Alternatively, in others, it could be a successful inversion of the disposition effect.)
- Holding Period: For a subset of portfolios (20%), holding period was an important variable in alpha generation. On average, these fund managers pick stocks that rise by 7.5% in their longest-held quintile of positions. This far outperforms other holding period quintiles, which all had negative average returns. Except, that is, for the very shortest-held 20% of positions, where picks generated 1.7% of alpha! Again, there are several possible interpretations of these results. That middle 60% of positions, for instance, may simply represent the positions that didn’t work out; an acceptable cost of business. Our experience, however, tells us that this middle ground is a source of lost alpha, and that more often than not, managers had the opportunity to take remedial action sooner.
Our hypothesis going into this project was that we were going to find a short list of “alpha leaks” that active managers in general tend to suffer. But that wasn’t the case. We found, instead, a wide array of factors that affect alpha both positively and negatively, and very little consistency across the portfolios.
But we were able to identify sources of alpha generation and/or destruction in all portfolios — within a set of factors that are consistent, identifiable and measurable in every case. We think these are incredibly encouraging findings for active managers; once identified in their own portfolio, these can be corrected and optimized, with potentially significant benefits to their returns.
Technical details of our methodology are proprietary, but can be shared with interested and qualified investment professionals by request. If you’d like to like to receive them, please complete the form below.
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