By Michael A. Ervolini, Distinguished Fellow, FactSet Research Systems, Inc.
Behavioral Matters is a series of essays on the application of Behavioral Finance written specifically for professional investors and portfolio managers.
"Good decisions come from experience. Experience comes from making bad decisions.” - Mark Twain
Active resizing of positions is one way managers attempt to capture incremental alpha. They add to position size in hopes of riding a price bounce and trim to minimize the effects of a drop. New analyses reveal that for the most part they would be better off avoiding such interim trading. The reason adds and trims rarely help is poor feedback Interim trading is perhaps the least calibrated aspect of active management, despite its industry wide popularity. Which begs the question: Can adds and trims be substantially improved, or should they be used exclusively to support flows and risk management? This essay first examines the role that poor feedback plays in fostering ineffective interim trading decisions, then considers the psychological forces perpetuating this problem, and continues by describing how rigorous feedback is being used to improve sizing regimes.
SUMMING ADDS AND TRIMS
Adds and trims are used extensively within equity portfolios as a means of bolstering portfolio results. Their net impact, however, typically falls far short of this intention. Analyses of hundreds of portfolios involving over 4.5 trillion in assets indicates that most managers would be better off if they avoided interim trading. One recent study shows that adds and trims combined generate negative to neutral results for more than four out of five equity portfolios.1 The reason that adds and trims fail to provide positive results for most managers is that these actions frequently reflect heuristics rather than calibrated processes. They are actions driven by hope and mistaken understandings of which decisions really are driving results.
Conventional analytics (i. e. attribution, hit rate, vacation report, etc. are at the root of the problem. These measures are effective for assessing overall portfolio composition and its relationship to performance. They are, however, weak proxies for quantifying investment skills, like adding and trimming. This creates a poor feedback environment wherein actions taken cannot be accurately mapped to outcomes. In such environments imagination and emotions become surrogates for data and thoughtful analysis. Well before conscious deliberation even gets warmed up, such emotionally shaped impressions are forged into beliefs. The result is incorrect learning or more precisely mislearning.
“Adds and trims combined generate negative to neutral results for more than four out of five equity portfolios.”
Investment choices are the outcome of what Daniel Kahneman describes as Dual Systems thinking.2 According to this model, System One is rapid fire, arriving at decisions automatically within the unconscious, highly dependent on heuristics, and is readily influenced by our emotional state. System Two, in contrast, is slower, involves conscious deliberation, and more prone to focus on facts versus feelings. In environments where the data is noisy, the feedback weak, and uncertainty abounds decisions are much more apt to reflect System One thinking over that of System Two. This means that individuals frequently arrive at investment decisions that they perceive as well reasoned even though their choice may be more in line with unconscious thinking. Thus, no matter how well conceived an interim trading decision may feel, its motivation is frequently related more to a heuristic or the eruption of an emotion rather than sound analysis.
This situation can lead to what psychologists refer to as learned carelessness. Researchers Raue and Schneider describe learned carelessness as follows: “By experiencing success without effort or through the repeated lack of negative consequences [feedback] people form and reinforce their perception that “everything is fine and will remain fine.3 If you remember those few adds and trims that seemed to work, while not receiving clear feedback regarding the less favorable interim trades, you open yourself up to a series of careless choices. Ironically, thinking harder in those moments when an add or trim is being pondered mostly serves to make fragile choices seem analytically robust. This is particularly the case where well calibrated decision processes are not in place. Remarking on this phenomenon Raue and Schneider offer: “People might believe that they have analyzed all the options, went through all the pros and cons, and made a good decision based on the given facts, but often they already feel the answer all along. 3
A MORE DISCIPLINED PROCESS
Taking the guesswork out of adds and trims requires rigorous analysis. The type that can isolate each decision, compute its efficacy, and pull these results together into a measure of skill.
One such method is illustrated in Figure 1. The results shown specify add and trim skills for positions having unrealized gains at the time of trade (up) or unrealized losses (down). It can be seen that all adds made to this portfolio (Add Up and Add Down) were, in aggregate, not helpful, costing the portfolio 100 basis points and 48 basis points per year, respectively (red bars). The trimming skill is split, with Trim Up hurting returns by 61 basis points (red bar) while Trim Down lifted portfolio results by 43 basis points (green bar). Clearly, interim trading is not benefiting this portfolio.
Equally important is knowing the persistence of each skill This can be approached by examining their year-by-year impact. The example presented in Figure 2 looks at the skill persistence for Add Up. The analysis shows that Adding Up was a consistent headwind to performance, producing negative results in ten out of thirteen years. Moreover, the magnitude of the negative years is much greater than that of the years where Add Up worked. In this example, Add Up is an undeveloped skill, diminishing rather than improving portfolio results.
BLUSTEROUS CONVICTION
Accentuating individual propensities for mislearning is a strong effect that groups and organizations can play. The active management industry has functioned in the absence of robust feedback pretty much since its inception. In order to resolve frequent bouts of internal struggle regarding which choice to take or even if a decision is necessary, fundamental portfolio managers have relied on a special attribute known as conviction. At its best conviction encompasses all available and pertinent information together with the professional judgment of the manager, arriving at a decision that is more likely than not to help the portfolio. At other times conviction is simply hubris manifested by the unconscious need to resolve uncertainty and the dissonance it brings.
Reliance on uncalibrated processes limits the effectiveness of conviction. This problem gets magnified in teams where the need to feel confident about decisions is a group norm, explicit or otherwise. Elaborating on this point, Raue and Schneider point out: “If one observes that other people succeed with careless behavior, one will be more likely to show the same behavior. Furthermore, the more similar these other people are to oneself, the likelier it is that one will adopt the behavior.3
TURNING THE TIDE
Using the type of rigorous feedback highlighted it is possible for portfolio managers to both become much more self-aware of their unique strengths and shortcomings and to then use this newfound knowledge to improve. Initial efforts likely will focus on avoiding alpha depleting activities as are so often found amongst adds and trims. For example, the portfolio studied might consider dispensing with Adding Up as an initial step. From there, the team can engage in further analytic investigations into their Add Up skills. Additional studies might include increasing granularity, such as measuring Add Up within sectors, with regard to an array of attributes or factors, coincident to analyst ranks or multi factor model scores, and cross sectionally. Such analysis is likely to uncover distinct situations where current Add Up
does work, and illuminate potential remedies where retooling is needed.
CONCLUSION
There has never been a time when capturing incremental alpha was so clearly needed. One place to look is in the adds and trims that comprise the interim trading within actively managed portfolios. Traditional metrics are unable to measure skill in any meaningful fashion merely maintaining the status quo of weak learning. This situation has, in turn, led to the overreliance on untested conviction resulting in frequent poor choices.
New types of analytics are providing insights long hoped for within active management. They deliver rigorous feedback about skills and identify precise opportunities for improving. These new investigative tools can enable managers to enhance their conviction while diminishing the need for hubris. Not pursuing the use of such analytics might just be, well careless.
End Notes:
1. Cabot Investment Technology, Inc unpublished research assessing the adds and trims across scores of actively managed equity portfolios, May, 2020
2. Daniel Kahneman,Kahneman,“ Fast and Slow,” Farr, Straus and Giroux, 2011
3. Martina Raue and Elisabeth Schneider, Zero Risk Bias, Feelings and Learned Carelessness, Psycological Perspectives on Percieved Safety, Chapter 5 Springer, Nature, 2019
All posts are the opinion of the contributing author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CAIA Association or the author’s employer.
About the Author:
FactSet makes financial decisions work. It’s done through the delivery of highly curated information such as company fundamental data, ESG data, quantitative factors, regulatory compliance and much more combined with industry leading analytics and services. The Company supports decision-makers across all financial industries including banking, asset management, private equity, hedge funds, insurance companies, pension funds, investment advisory, sovereign wealth funds and endowments.
Mike Ervolini is best known for his work involving the application of behavioral finance, psychology, and neuroscience to decision making under uncertainty. Mike has written extensively on the challenges of active management including his book: “Managing Equity Portfolios – A Behavioral Approach to Improving Skills and Investment Processes,” MIT Press.
Mike joined FactSet in June of 2021 when the Company purchased Cabot Investment Technology, Inc., of which Mike was Founder and CEO. Cabot is the leading developer and provider of behavioral analytics for active equity management. Prior to Cabot Mike was the Founder and CEO of Charter Research LLC, a fintech business that developed and marketed high performance analytic software for the commercial mortgage-backed securities (CMBS) industry. Charter was purchased by Standard & Poor’s, a McGraw-Hill company. Previously Mike worked for AEW Capital Management LLC of Boston and Latimer & Buck, Inc., a division of Legg Mason.
Mike brings to FactSet over 35 years of senior executive experience in finance, asset management, analytics, sales and marketing. In addition to furthering the integration of the Cabot technology across the FactSet platform Mike is spearheading the Company’s enhanced thought leadership efforts and guiding FactSet’s expansion within the so-called front office or C-suite.
Mike earned a BA in Economics from Rutgers University and a MS from the University of Pennsylvania.