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Where To Look For Skilled Equity Managers

Smart Thinking Issue 6
ESSAY

Where To Look For Skilled Equity Managers

Behavioral Matters: Insights from the application of Behavioral Finance | Issue 6

Written by Michael A. Ervolini

4 min read

Where To Look For Skilled Equity Managers

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INTRODUCTION

Skepticism regarding the existence of skilled equity fund managers is understandable. In most years the majority of actively managed equity funds underperform.[1] Among those that do outperform few manage to do so for 3, 5, or 10 years in a row.[2] Then there is the direct experience that most asset owners and allocators share: conducting a search for a new equity manager, performing rigorous due diligence, establishing a short list, selecting the final candidate, and making an allocation. Then watching with a mixture of surprise and dismay as the once high expectation fund delivers quarter after quarter of underperformance. It is no wonder why so many institutional investors have grown timid about allocations to actively managed equities.

However, not all asset owners and allocators are frustrated by their active equity programs. In fact, many capture meaningful alpha from their actively managed equity investments. They do it by more fully understanding the skill of their fund managers. This added knowledge enables them to sharpen their fund assessment processes and make better allocation decisions. This translates into the majority of their allocations outperforming in any given year. The managers of their funds are not perfect or super stars. They are what Inalytics LTD refers to as elite managers. Working with elite managers can tilt the odds in favor of earning alpha more frequently than not.

WHAT INALYTICS UNCOVERED

In their 2022 research paper Inalytics evaluated a group of 752 actively managed equity funds.[3] Among this group 630 or 84% outperformed their benchmarks for the prior three years. Whereas 122 or 16% underperformed. Clearly this group is not representative of the overall active equity industry. It consists of funds chosen to be analyzed by clients of Inalytics. Each fund had already gone through the gauntlet of traditional fund due diligence. Therefore, it is not surprising that the majority of these funds were generating excess returns. What is impressive is that the outperformers provided an average 397 basis points (bps) of after-cost alpha over the analysis period. Moreover, the Inalytics investigation showed that strong buying, or what they term the “research process”, drove fund results. Skilled buying , they computed, provided 319 bps of fund excess returns. This equates to 104 percent of the average excess returns for the outperforming group. Inalytics also observed that the sizing skill slightly impaired results, contributing (11) bps of alpha. Neither rebalancing position weights (adds and trims) or selling skills seemed to have a material impacts on fund returns according to their study.

It is worth pointing out that the skill or skills that most contributed to excess returns might vary when analyzed by the other decision-based analytics.[4] The potential for differing skill measures stems from the varying methods used in computing skills across the providers.[5]

CONCLUSION

The Inalytics research makes clear that quantifiable skills are responsible for fund excess returns in many instances. Subsequent analyses by Inalytics and other decision-based skill analytics providers confirms this observation. The analysis also underscores why a growing number of asset owners and allocators are incorporating decision-based analytics into their fund assessment processes.

By using these newer analytics investors know much more about the true skill of their equity managers (external and internal). They can also assess the consistency of skills that are most responsible for benchmark-beating results. Which means these investors have deeper insight into which managers are more likely to deliver positive alpha going forward. Now that sounds like smart investing.

ENDNOTES

  1. “SPIVA® Year-End 2025,” reports for U.S. and globally. https://www.spglobal.com
  2. “S. Persistence Scorecard Year-End 2024 – SPIVA. https://www.spglobal.com
  3. “Investment Skill: Does It Exist and What Does It Look Like?”, Inalytics LTD, Spring 2022.
  4. Michael A. Ervolini, Skill Versus Luck – Taking The Guessing Out Of Equity Fund Selection, MIT Press, February 2026.
  5. Ibid.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Active Share Is No Indicator of Manager Skill

Smart Thinking Issue 4
ESSAY

Active Share Is No Indicator of Manager Skill

Behavioral Matters: Insights from the application of Behavioral Finance | Issue 4

Written by Michael A. Ervolini

5 min read

Active Share Is No Indicator of Manager Skill

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INTRODUCTION

Actively managed equities continue to receive significant allocations from all manner of investors. Among the group commonly referred to as institutional asset owners (e.g., sovereign wealth funds, pension funds, endowments, insurance companies, banks, family offices, and builders of multi-asset products), actively managed equities remain an important staple within their allocation line-ups. Yet, many of these asset owners find it extremely difficult to identify truly skilled managers from among the many competing for their capital. Relying exclusively on conventional portfolio analytics has done little to improve the fund selection process. Conventional analytics are very helpful in understanding a fund’s past results and how they were generated. However, they offer very little insight into manager skill.

Not long ago the concept of active share was introduced to enhance fund selections. It was believed that this analytic could help identify skilled equity managers. Over time it became clear that active share is a helpful metric in assessing how closely a fund’s position weights match those within its benchmark. On the other hand, its ability to identify skilled managers has proven to be no better than that of other conventional analytics.

THE SIREN SONG OF HOPE

In 2009 the asset management industry was abuzz with a paper by Martijn Cremers and Antti Petajisto describing a novel portfolio metric termed active share. The authors defined active share as one-half of the sum of the absolute values of the differences in weights between all positions held in an equity fund and their weights in the fund’s benchmark. (1) Which means active share quantifies how similarly or differently a fund’s capital is deployed relative to its benchmark. Greater active share indicates more benchmark divergence. Smaller active share indicates less benchmark divergence. The thinking being that the lower the active share (i.e., more similar a fund’s position weights match their benchmark weights) the harder it is to generate excess returns. Conversely, the larger the active share the more bets the manager has made and thus the greater the potential to outperform, at least conceptually.

In their paper Cremers and Petajisto reported that higher active share was correlated with stronger fund results. They went even further to say that active share provides a meaningful indicator of manager skill and can also help predict future fund outperformance. As explained by the authors: “Active Share predicts fund performance: funds with the highest Active Share significantly outperform their benchmarks, both before and after expenses, and they exhibit strong performance persistence.” (2) The availability of a straightforward metric and its ability to identify skilled managers proved alluring.Many asset owners and allocation professionals quickly integrated active share into their equity fun assessment processes.

The results were far less than hoped. A number of highly active share funds did outperform for years and some did so for shorter periods. Asset owners lucky enough to have allocations into the outperforming high active share funds did well. However, many high active share funds delivered only benchmark level returns or less. Asset owners unlucky enough to be invested in these lower performing high active share funds earned lackluster returns or worse. What happened? Why didn’t more high active share funds outperform as expected?

OUTCOME VS. SKILL

The fundamental problem is that active share like many other conventional analytics is a measure of fund outcome not skill. This fact is readily evident by considering the types of data they use as inputs. These data consist of a fund’s return series and its history of daily holdings. Since these data are themselves fund outcomes, they do not contain the information required to compute manager skill. What these two data types support effectively is the computation of analytics that describe how a fund was managed. Examples include information ratio, which indicates how much risk the fund took for each increment of excess return; attribution analysis, which describes how much of a fund’s excess return came from stock selection versus sector allocation; and multi-factor regression analysis, which explains which factor exposures had the largest impact on results. It is one thing to explain how past results were generated. It is very different to identify which manager skills added to or detracted from the fund’s excess returns. The latter requires thinking anew about what constitutes skill and how it should be computed.

CAUSE AND EFFECT

Measuring skill requires relating manager decisions to the outcomes they generate. It involves linking cause and effect. In my latest book Skill Versus Luck, I describe how skill identification and quantification are being done using what are termed decision-based analytics. (3) Decision-based analytics isolate and group distinct types of decisions made by a fund manager. These include initiating new buys, selling out of positions, and adjusting position sizes. The impact of these decisions is then computed. It is done by reversing a single type of decision to create an adjusted fund history. Comparing the results of the actual fund to those of the adjusted history indicates the level of skill reflected in those decisions. If the actual results are greater than those computed from the adjusted history the skill is positive, in an amount equal to the difference. Alternatively, if the actual results are less than those computed from the adjusted history the skill is negative, in an amount equal to the difference.

Here is how it works conceptually. Consider assessing a manager’s skill at adding capital to losing positions. A management tactic that is often referred to as adding on the way down. Measuring the manager’s skill at this involves first identifying each time over the fund’s history more capital was added to positions whose price had recently dropped. Then an adjusted history would be created in which each such add would be reversed – the additional capital would be subtracted from the position whose price had recently dropped. Then the excess returns for the adjusted history would be computed. The difference between the excess returns of the actual fund and those of the adjusted history would indicate the manager’s skill at making these incremental investments.

A number of asset owners are using decision-based analytics today to strengthen their fund assessment processes and make more effective allocation decisions. (4) These investors are benefiting from a deeper understanding of which manager skills are helping to generate excess returns as well as the persistence of such skills. Decision-based analytics are also helping asset owners confirm elements of each manager’s investment processes – further informing likely repeatability of success going forward.

CONCLUSION

Identifying which funds have recently outperformed is straightforward. Knowing if such outperformance is based on inconsistent or lucky decisions versus manager skill remains a challenge. Active share was initially believed to possess information able to identify skilled managers. This is no longer the case and active share is now viewed as a useful metric for understanding a fund’s position bets versus benchmark tracking. It’s demotion regarding skill assessment was confirmed in a later paper by Cremers himself: “It is only for managers with strong individual stock picking skills that a high Active Share may be beneficial.” (5) In other words, high active share accentuates position bets much like leverage. Positions with large active weights are able to contribute substantial positive or negative returns to a fund. Ultimately the direction and magnitude of the returns from high active share positions depends upon fund manager skill.

Fortunately, newer decision-based analytics provide unambiguous measures of fund manager skill. When combined with conventional analytics these newer skill metrics enable asset owners to better understand manager ability and make more effective allocation decisions.

ENDNOTES

  1. Martijn Cremers and Antti Petajisto, “How Active is Your Fund Manager? A New Measure That Predicts Performance,” The International Center for Finance at the Yale School of Management, March 2009.
  2. Ibid.
  3. Michael A. Ervolini, “Skill Versus Luck – Taking The Guessing Out Of Equity Fund Selection,” MIT Press, February 3, 2026. Available for pre-order on Amazon.
  4. Ibid.
  5. Martijn Cremers, “Active Share and the Three Pillars of Active Management: Skill, Conviction and Opportunity”, Financial Analyst Journal, 2016.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Broadening Diversification To Include Skill

Smart Thinking Issue 3
ESSAY

Broadening Diversification To Include Skill

Smart Thinking: A Skill Versus Luck Essay Series | Issue 3

Written by Michael A. Ervolini

8 min read

Broadening Diversification To Include Skill

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INTRODUCTION

Few investors, if there are any, doubt the benefits of diversification. Deciding precisely how to achieve it, however, remains a thorny challenge.

SEEKING DIVERSIFICATION

The practice of diversification (AKA risk management) gained considerable analytic rigor with the 1952 paper “Portfolio Selection “by Harry Markowitz. (1) In his paper Markowitz informs us that a portfolio’s riskiness is not simply the average risk of the assets or funds it owns. Instead, portfolio level risk is based upon the degree to which the prices of the various assets and funds move together. Said differently, do portfolio assets and funds provide offsetting or compounding riskiness? Assets and funds with positively correlated price movements tend to exacerbate risk while those whose price movements are uncorrelated or negatively correlated ameliorate it. One of Markowitz’s enduring contributions is showing that many sources of risk can be analytically identified, quantified and, therefore, managed.

Diversification and risk analytics have been greatly expanded since the 1950s. Within equities alone this includes the analysis of asset price movements in relationship to company location (country, global region) and relative to a host of factor exposures, such as market value (size), financial dynamics (growth vs. value), price momentum, balance sheet quality (debt levels), and earnings growth. These and similar characteristics are commonly integrated into portfolio construction processes. The intended result is a portfolio whose assets are sufficiently diverse such that the net effect provides an attractive trade-off between quantifiable risks and hoped for returns.

The diversification benefits from many traditional factors are in decline according to numerous studies. (2) This may be due to the effects of globalization and/or other market forces. What’s clear is that more positive correlations are now being observed among a number of traditional diversification characteristics. This dynamic, in good part, motivates the continued search for newer and alternative sources of incremental diversification.

THE HUMAN FACTOR

One idea that is gaining traction involves expanding the sources of diversification to include fund manager skill. While this may seem obvious implementing it has become possible only recently due to newer analytics. Traditional efforts to capture elements of manager skill have relied upon conventional analytics such as relative return, multi-factor alpha, attribution, upside/downside capture, information ratio, and active share. These metrics are very helpful in describing how an equity fund has performed. They say little about manager skill, however. Their shortcoming with regard to describing skill is inherent in the data they use. These data consist of two forms of outcome, namely fund returns and/or daily holdings. The outcome-driven results they produce can only hint at the presence or absence of skill. These analytics cannot identify nor quantify skill directly.

Fortunately, newer analytics for computing skill now exist. These newer analytics use as inputs the decisions made by the fund manager. These newer methods are referred to as decision-based analytics. These newer analytics relate the decisions made by the manager with the returns they generate. They connect cause and effect. This is precisely how skill is computed in other demanding endeavors like sports, auto racing, jet piloting, and surgery. These newer analytics provide capital owners and allocators enhanced insights into manager skills, decision consistency, and heretofore undetectable sources of risk. (3) Examples of how these newer analytics are helping asset owners and allocators are discussed next.

BETTER INSIGHTS, BETTER DECISIONS

Incremental diversification can be captured through the use of manager skills. Importantly, it is accessible even from funds whose managers are pursuing the same style and strategy. This opportunity exists when the stocks they purchase reflect different alpha time horizons or alpha generating profiles. (4) One manager might buy stocks that typically take off soon after initial purchase and continue to generate excess returns for 9 to 18 months (relatively fast and short time horizon). A second manager with the same mandate might be purchasing stocks that are slow to show any price movement but once they get going can generate alpha for two and three years or more (slow starters with extended time horizon. These two managers are fishing in essentially the same pond for the same species. Yet the fish they land are quantifiably different.

Alpha time horizon and other manager skills are now being used by JANA Investment Advisers, a manager search and OCIO consultancy. According to Justin Tay, JANA’s Head Of Global Equity Research: “Knowledge of a manager’s alpha time horizon can support allocations to multiple top managers even in the same style –while avoiding overlapping decision processes. It’s a subtle but important form of diversification.” (5) This type of diversification can improve the odds of capturing the full potential from each style/strategy blend by finding managers whose buy processes yield stocks that outperform over different time horizons. 

Another aspect of skill involves the management of significant losers, defined as positions down by 20% or more. Some managers are skilled at culling out significant losers unlikely to recover and/or retaining those that eventually do rebound. The opposite also is observed where managers are too quick to sell depressed stocks which soon rebound and/or have trouble letting go of weak positions that never recover. Knowing how effectively managers (even great ones) deal with significant losers provides additional insights into how risky a fund may become in a market downturn.

Then there is the question of position sizing. Deploying meaningful capital into stocks before or as soon as they begin to take off enables funds to capture the full benefit of strong buys. In contrast, habitually under sizing or chasing strong buys undermines the potential available from purchases that outperform. Knowing how effectively a manager builds up their best buys (winners) can shed light on the likelihood of capturing excess returns going forward.

These and other newer analytic results are enabling asset owners and allocators to better assess equity managers and strengthen their allocation processes.

IT’S CATCHING ON

Increasingly investors are integrating the newer analytics into their equity allocation processes. Pension funds and sovereign wealth funds are using the newer analytics to both assess external allocations and to obtain clearer insight into how effectively internal teams are managing their equity funds. Endowments, Family offices, and large asset management companies are using the newer analytics to better understand the strengths and shortcomings of their third-party equity managers. The results include a deeper understanding of which skills are driving results and which skill deficits may represent previously unknown risks. The insights obtained also support more productive discussions between investors and fund managers – during due diligence, at regular update meetings, and especially when fund results are disappointing.

CONCLUSION

Portfolio diversification is a common objective. Globalization and other market forces are increasing the correlation among various diversification characteristics (e.g., funds, asset types, factors). Stronger positive correlations make diversification ever more difficult. 

In response asset owners and allocators are expanding how they view and implement their approaches to diversification. One transformative effort underway is the integration of manager skills as an additional alpha and risk characteristic. Doing this requires use of newer decision-based analytics. These newer analytics provide superior measures of manager skill by relating decisions taken by a manager to the impact such decisions have on fund results.  

It’s time. Time to improve the industry’s knowledge about manager skill. Time to capture more effectively the potential available from actively managed equities. Time to make better equity allocation decisions.

ENDNOTES

  1. Harry Markowitz, “Portfolio Selection,” The Journal of Finance, Vol. 7, No. 1. (Mar. 1952), pp.77-91.
  2. For example, see: Richard Yasenchak, “Correlation Conundrum: How Will You Fix Portfolio Diversification?,” Intech Investment, Inc., March 8, 2023. https://www.intechinvestments.com
  3. Michael A. Ervolini, “Skill Versus Luck – Taking The Guesswork Out Of Equity Fund Selection,” MIT Press, February 3, 2026. Available for pre-order on Amazon.
  4. A fund’s alpha generating profile or information advantage indicates, on average: when new stock purchases begin to outperform, how much excess return they generate, and when outperformance tends to be depleted.
  5. Interview by the author with Justin Tay, Head Of Global Equity Research, JANA Investment Advisors, Inc., June 2025.
Michael Ervolini headshot

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Essays

Making Active Equities More Stylish

Smart Thinking Issue 2
ESSAY

Making Active Equities Mo

Smart Thinking: A Skill Versus Luck Essay Series | Issue 2

Written by Michael A. Ervolini

5 min read

Making Action Equities More Stylish

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INTRODUCTION

Style analysis is used regularly to support equity fund assessment and allocation decisions. While this analytic offers useful insights, its value in determining a fund’s desirability may be more limited than generally perceived. It can deliver unintended consequences that diminish rather than enhance ultimate outcomes. This essay clarifies the benefits available from style analysis and offers an improved approach for its use in supporting active equity fund assessment.

GOT STYLE?

In his landmark 1988 paper “Determining a fund’s effective asset mix”, William F. Sharpe described a method for assessing the style characteristics of an equity fund.*1 Since then style analysis has become an integral element of fund assessment, allocation decisions, and confirmation that a fund is acting in accordance with its strategy and purpose (i.e., identifying style drift).*2

The debate continues regarding whether Sharpe’s return-based analysis or the alternate holdings-based method yield the more creditable result.*3  The returns-based approach resolves which asset indices best explain (i.e., are most correlated) with the return series of a fund or portfolio. Return-based style analysis is commonly referred to as a top-down approach. Holdings-based analysis takes a more bottom-up path by first determining the style or factor characteristics of each of a fund’s holdings over time. For example, some holdings may be more growth oriented while others more value oriented. Factor levels are then aggregated across holdings to formulate the fund’s overall style.

WHAT YOU GET

Both approaches have their strengths and shortcomings. But each serves a basic role in fund assessment. In the words of Sharpe: “All that style is is exposure. If I say your style is 60% growth and 40% value that means you’ll move 0.6 times whatever happens to growth stocks plus 0.4 times whatever happens to value stocks.”*4

The algebra cited by Sharpe holds to the extent that the fund continues to be managed in the future much the way it was managed in the past. Meaning that the fund owns an array of stocks such that the returns going forward, or the factor composition of its holdings are based on similar bets as were previously taken (i.e., exposures to large/small caps, growth/value, interest rates). 

A diversified fund that is highly consistent in the stocks it owns fits this bill. So does a diversified fund that rotates from one factor to another regularly. Style analysis can be less helpful for a highly concentrated fund. Here a couple of positions can dominate the fund’s factor exposures. And the dominant positions can change in response to market forces rather than manager intention. This can result in substantial style shifts that may be of limited value in estimating future exposures. A similar diminution in usefulness of style analysis is encountered for a fund that has recently and permanently changed its strategy or alpha sourcing. Although it is important to be mindful of these two latter considerations the bigger issue is the frequent misapplication of style analysis and the unintended consequences therefrom.

THE STYLE TRAP

What can style analysis say about effective fund management? In good part it depends on the question being investigated. One common use of style analysis is the assessment of style drift. Drift is indicated by a set of current factor exposures that differ meaningfully from the fund’s historic exposures (i.e., the style changed). Typically, the desired outcome is the absence of style drift or, stated in the affirmative, consistent factor exposures. However, exposure consistency frequently comes at a high cost.

Consider a value fund. It is fully expected that this fund is purchasing mostly (if not exclusively) stocks with a clear value signature. Which means that at time of initial purchase these stocks fit the value style. But what about new buys that then go on to generate significant excess returns? As these positions experience improving fundamentals and upward price movement, they begin to shed their value characteristics and edge into growth territory. One assumes that this evolution is a primary reason for buying value stocks in the first place. The intention being that enough of these value stocks will outperform sufficiently so that the fund itself can generate excess returns.

All too often, however, value funds significantly trim or liquidate their strongest performing positions prematurely. These actions are taken well before such successful buys have exhausted their ability to generate excess returns. It’s done to ensure that the fund is not perceived as drifting outside of its value style box. Managers that engage in such activities believe it is what clients want. They are often told that: “The client is allocated to the fund based, in good part, on its style or factor exposures. Departures from historical style are likely to complicate (or even compromise) the client’s overall risk management.” In Such situations adherence to style or overall factor exposures supersedes the capture of excess returns. Clearly, managing risk indirectly through style allocations brings with it unintended consequences.

GOING STYLISH

There is an alternate and for many better ways of confronting the question of style. It involves selecting funds based on the types of stocks they purchase rather than all the stocks they own.*5 Within this formulation value funds are expected to purchase value stocks, growth funds are expected to purchase growth stocks, and so forth. Once a position is established, however, the fund is then expected to maximize its contribution to excess returns subject to prespecified levels of risk control. This enables value fund to own growthy stocks that were initially purchase when they were clearly value. It allows a small cap fund to own mid cap stocks that have performed well and grown out of their small cap designation. It improves the potential for funds to realize excess returns while purchasing stocks that fit a specific style designation.

Allocating to funds that operate as described requires some rethinking and retooling on the part of asset owners/allocators. In particular they need to take a greater role in managing the overall risk exposures across their equity platforms. By analyzing the complete set of all their equity positions (internally and externally managed) they are able to offset over and under exposures more comprehensively. And in doing so they give a greater degree of freedom to each manager that can be used in the pursuit of excess returns.

CONCLUSION

Actively managed equities continue to be an important asset class for many investors. Institutional asset owners/allocators can increase the value available from this asset class today by focusing style analysis directly on the types of stocks being purchased rather than on conformity of fund overall exposures.  This will allow funds to hold on to their strongest positions longer and capture even greater excess returns. Replacing traditional style conformity and using a “purchase what is expected” approach is already helping a growing number of asset owners/allocators improve the results from their equity programs. These investors are capturing greater excess returns while making equity investing ever more stylish.

ENDNOTES

  1. William F. Sharpe, “Determining a fund’s effective asset mix,” Investment management review, 1988.
  2. “RETURNS – VS. HOLDINGS – BASED STYLE ANALYSIS”, Beacon Pointe Research White Paper, Beacon Pointe Advisors, LLC, September 2022.
  3. Paul D. Kaplan, “Holdings-Based And Returns-Based Style Models”, MorningStar, Inc. June 2023.
  4. Barry Vinocur, “Setting The Record Straight On Style Analysis”, A Newsmaker Interview, Stanford University, 1999, http://www-sharpe.stanford.edu/fa.
  5. Michael A. Ervolini, “Skill Versus Luck – Taking The Guesswork Out of Equity Fund Selection”, MIT Press, February 2026 (forthcoming).
Michael Ervolini headshot

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

Categories
Essays

Measuring Manager Skill Versus Fund Outcomes

Smart Thinking Issue 1
ESSAY

Measuring Manager Skill Versus Fund Outcomes

Smart Thinking: A Skill Versus Luck Essay Series | Issue 1

Written by Michael A. Ervolini

3 min read

Measuring Skilled Managers Versus Fund Outcomes

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Active equity investors want their capital in the hands of skilled managers.

The reasoning is straightforward: Managers with the greatest levels of skill should do better than their less skilled peers over time, all other things being equal. Identifying who is highly skilled and who is less so, however, remains a difficult if not utterly impossible task for most investors. And make no mistake about it, this problem is equally vexing to large and highly sophisticated asset owners as well as individuals.  The inability to effectively assess skill lies in the analytics commonly used for such investigations. Such conventional analytics provide useful information for sure – just not about skills.

What’s meant by conventional analytics is the myriad of metrics regularly used in support of fund assessments. These analytics include relative return, multi-factor alpha, information ratio, upside/downside capture, active share, attribution, hit rates, batting average, and slugging ratio. These metrics are effective in describing how a fund generated its returns. They indicate whether the fund’s returns were the result of high concentration, market factor cyclicality, wisely overweighting or underweighting sectors, or taking on additional risk (i.e., volatility). What these analytics cannot do is identify or quantify skill.

The reason is elemental. Conventional analytics are computed using a fund’s return series and/or its holdings history as their data. These data are themselves outcomes. They reflect the performance of the fund which constitutes its returns and also substantially determines the size of its holdings over time. These conventionally derived metrics, therefore, are referred to as outcome-based analytics. And while outcomes do reflect the presence or absence of skill they are not themselves measures of skill.

Meaningful measures of skill are found in the relationships between types of manager decisions and the results they generate. Said differently, skill measurement involves capturing cause and effect. A golfer’s skill is not measured by how many games they win. It is assessed by the distance and placement of drives off the tea, the ability to hit shots with irons close to or onto the green, and the accuracy of the putting. As each of these skills improve we’d expect the golfer to achieve stronger results (i.e., win more games).

As mentioned, manager skills are observed by investigating specific decisions or actions taken and the results they generate. Examples of manager skills that can be isolated and calculated include:

  • Buying new stocks that more often than not outperform their sectors or benchmarks.
  • Selling positions such that the alpha from strong stocks is captured while the drag from underperforming stocks is minimized. 
  • Sizing positions so that sufficient capital is invested in the strongest stocks (i.e., allowing them to lift overall fund returns).

Metrics such as these reflect what are known as decision-based analytics. These analytics capture the cause and effect relationships between manager actions and fund returns. They provide unambiguous measures of skill. Using the results of decision-based analytics enables investors to more effectively assess a fund’s desirability and to make better allocation decisions.

Currently there are a number of firms which provide decision-based analytics.1  The question that the industry needs to address is why aren’t these superior measures of skill being used regularly today? Absent such analytics investors simply cannot make their best decisions, which can lead only to bad outcomes for all market participants.

ENDNOTES

  1. Firms providing decision-based analytics include: Inalytics, LTD, FactSet Research Systems, Inc., Alpha Theory LLC, Essentia Analytics LTD, and Behavioral Lab LTD.
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MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Essays

Counterfactual Investing

ESSAY

Behavioral Matters: Insights from the application of Behavioral Finance | Issue 14

Written by Michael A. Ervolini

8 min read

Counterfactual Investing

“So we have the paradox of a man shamed to death because he is only the second pugilist or the second oarsman in the world. That he is able to beat the whole population of the globe minus one is nothing; he has “pitted” himself to beat that one; and as long as he doesn’t do that nothing else counts.”

– William James

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INTRODUCTION

Imagination and creativity help turn good ideas into winning strategies and great picks if they are calibrated to ensure favorable results. Imagination also can push investors toward unproductive decisions — ones that feel right while lowering performance. Known as Counterfactual Thinking, this type of deliberation can affect your interpretation of results and can shape the buys and sells you make.

DARN, I JUST MISSED IT

Emotional responses to outcomes often are influenced by what might have been. Counterfactual Thinking, as such thoughts are known, often ends in regret. The emotional response to an event depends on how easily one can conjure up alternate outcomes that are either better or worse. An often cited example regards missing a flight by five minutes or 45 minutes. People that just miss their flight tend to kick themselves more than those who missed their plane by a mile. The closer you were to making the flight, the easier it is to construct an alternative outcome or counterfactual that triggers regret.

WHEN WORSE IS BETTER

Who should be happier, the person that wins the silver medal or the bronze? The silver medal winner is objectively better off — he or she is closer to gold than the bronze medal winner. Yet, that is precisely why a silver medalist enjoys second place far less than the bronze medalist enjoys coming in third.

In analyzing medal winners from both the Olympics and the Empire State Games, researchers Thomas Gilovich, Victoria Husted Medzec and Scott Madey found that silver medalists were less happy with their accomplishment than bronze winners. The silver medalists created a counterfactual based on not having won gold, focusing upward and ruminating about how close they came to first place. This thinking induced feelings of regret and frustration… the, if-only-I-hads. The bronze medalist, in contrast, focused downwards and formulated a more positive counterfactual. Rather than being among the others hitting the showers, they were at least up on the awards pedestal and very happy to be there. Counterfactual Thinking does more than color how we feel about past events; it can also trigger surprising actions.

PHANTOM GAINS AND LOSSES

Investors sometimes generate counterfactuals when they consider repurchasing previously owned stocks. In their paper “Once Burned, Twice Shy” Terrance Odean, Michal Strahilevitz and Brad Barber observed that investors are more likely to repurchase a stock when its current price is below that at which it was sold, and less likely to repurchase it when the current price is higher. The counterfactuals motivating these choices are explained as: “Investors who buy a stock at a lower price than they previously sold it experience the pleasure of knowing they are better off than if they had never sold that stock. Investors who buy a stock at a higher price than they previously sold it are painfully aware that they are worse off than if they had simply never sold that stock.” The terms “knowing” and “being aware“ express the feelings investors have about these purchases based on their if-only-I-hads.

The more relevant question for these investors is whether any stock they previously owned is likely to outperform alternate stocks going forward. For example, repurchasing a stock at a price higher than at what it was sold might be a good investment decision — even though it might feel bad. The counterfactuals make the investor feel a loss or gain based on price movement when the stock wasn’t even owned. This distracts from focusing on today’s thesis and how the stock will perform going forward. The result can be murky judgment — where emotions emanating from if-only’s override objective analysis.

CAN’T WIN FOR LOSING

Counterfactuals also shape the choices made when adding to current positions, according to Odean et al. Investors tend to add less frequently to holdings whose price has gone up, since being purchased (“winners”) and add more frequently to those whose price has dropped (“losers”). The counterfactual created for winners is, “I should have purchased more when it was cheap.” Investors prefer to avoid feeling the regret that this counterfactual brings, so they tend to avoid these buys. The counterfactual for buying losers seems to be associated with avoiding the pain of losing, as in, “If I buy more now and the price moves up, I can regain my current losses.” This counterfactual is consistent with Prospect Theory and resetting one’s reference point. The team’s research demonstrates, however, that the investors were no better off preferentially adding to losers over winners. Feeding their counterfactuals did not enhance their returns.

CONCLUSION

Counterfactual Thinking can hurt performance. It has the power to make silver medalist feel worse than those taking bronze. It can drive investors to make decisions based on if-only’s rather than facts. Counterfactuals can cause you to consider repurchasing stocks based more on price movement since being last sold than on current thesis. They can also cause you to refrain from adding to current portfolio winners… perhaps missing a huge run-up in the bargain. Selfawareness counters such ineffective thinking — keeping decisions factual.

ENDNOTES

  1. “When Less Is More: Counterfactual Thinking and Satisfaction Among Olympic Medalist”, Thomas Gilovich, Victoria Husted Medzec and Scott F. Madey, Journal of Personal and Social Psychology, Volume 69, 1995.
  2. “Once Burned, Twice Shy: How Naïve Learning and Counterfactuals Affect the Repurchase of Stocks Previously Sold”, Terrance Odean, Michal Strahilevitz and Brad M. Barber, Working Paper, September 2004.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Endowing Success

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Behavioral Matters: Insights from the application of Behavioral Finance | Issue 13

Written by Michael A. Ervolini

8 min read

Endowing Success

“The salesman knows nothing of what he is selling save that he is charging a great deal too much for it.”

– Oscar Wilde

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INTRODUCTION

Holding winners well past their alpha generation is a tendency recently identified among professional investors. These once highly productive buys inevitably devolve towards reversion to the mean, yet they seem to hold a special place in the minds (or is it hearts) of the managers. One explanation for holding winners too long is the Endowment Effect — valuing items higher when we possess them, making it more difficult to find a clearing price. This essay takes a look at the Endowment Effect and how it can impact the management of portfolio positions.

TRIALS OF BEING WELL ENDOWED

The Endowment Effect stifles selling. That is what Richard Thaler first suggested in 1980. The reasoning behind this theory goes like this: once a person possesses an item they then value that item more than prior to such possession. The item, it is believed, becomes part of the individual’s endowment and grows in value or importance for that reason alone. In other words, you would refuse to pay the same price for an item that you would want to sell it for. At first blush this might sound like simple horse-trading — buy low and sell high. But the roots of the Endowment Effect go deeper into our psyche.

Motivating this behavior is Loss Aversion. Taking a loss is an emotionally expensive experience. Studies suggest that the displeasure of losing $1 is two to three times greater than the pleasure of winning the same dollar. This asymmetry between winning and losing results in our avoiding losses in order to avoid the associated pain. Selling, it turns out, is perceived as a loss while buying tends to feel more like a gain. An implication of this asymmetry is that Loss Aversion will, on average, induce a higher dollar value for owners than for potential buyers, reducing the set of mutually acceptable trades.

NO MONKEYING AROUND

The sense of attachment we feel for possessions appears to be primal. Studies conducted by Keith Chen of Yale University involving Capuchin monkeys and Owen Jones at Vanderbilt University involving chimpanzees both support the notion that the Endowment Effect emanates from deep within our DNA.

The Capuchin monkeys were taught to trade coin-like tokens for food. They were offered similar amounts of food simultaneously at two windows in a specially designed pen. In any experiment, choosing one window would yield exactly the food offered, while choosing the other window would yield a 50/50 random chance of what was offered or a different amount. In one set of experiments the surprise amount was more than what was offered. In another set of experiments the surprise amount was less. After many trials, the monkeys showed a preference for choices where surprises were presented as bonuses rather than losses. They would choose the certain pay-out when they concluded the surprise was a loss; and choose the 50/50 pay-out when they concluded it provided a random gain. They exhibited classic Loss Aversion.

In a separate study chimpanzees were given a choice between peanut butter and frozen juice bars — both requiring time to fully ingest. Peanut butter was preferred by 60% of chimps when both treats were offered simultaneously. But when offered one at a time, only 20% of chimpanzees would trade. So while 40% preferred frozen juice bars, only 20% traded away their peanut butter when it was provided. Even more interestingly, while 60% showed a preference for peanut butter just 20% traded away frozen juice when it was provided. Their preferences apparently changed based on which treat they were given or possessed — a sure indication of the Endowment Effect.

THINKING IS ENDOWING

The sense of possession can be heightened merely by thinking about an item. In his 2008 paper, James Wolf discusses how exposure to an item (physical and mental) can increase feelings of ownership. He states “…that is, examining an item for longer periods of time resulted in greater attachment to the item and thus higher valuations.” Does the act of reviewing portfolio positions enhance their endowment?

It certainly is possible. Research suggests that analysis can promote enhanced feelings of ownership, which then inflates the value assigned to an item, in this case an equity position. Add to this scenario a position that has hit its current price peak and the stage is set for hesitancy in selling winners. Unfortunately, learning from our mistakes is a poor approach for overcoming the Endowment Effect. Studies indicate that market exposure — that is repeated attempts at essentially the same choice — does not result in eliminating the desire to over-value possessions. In other words, being a professional is no guaranteed defense against our unconscious motivations.

CONCLUSION

Managing positions is tough business and managing winners is no less so. The bias towards selling winners quickly has received tremendous attention in academic literature. The tendency to hold winners past their ability to generate alpha is less discussed, but has been shown to produce similar negative impacts on performance.

One explanation for holding winners too long is the Endowment Effect. We become fond of what we own… to a level where our selling price floats above what reasonable buyers are willing to pay. And the more we evaluate our winners the more difficult it may become to sell them without a sense of loss. Discipline, analysis and thesis confirmation may excite that monkey inside all of us and we… well… just go bananas.

ENDNOTES

  1. “How Basic Are Behavioral Biases: Evidence From Capuchin Monkey Trading Behavior”, Journal of Political Economy, 2006, by Keith Chen, Venkat lakshminarayanan and Lauri R. Santos.
  2. “Experimental Tests of the Endowment Effect and the Coase Theorem”, The Journal of Political Economy, Vol. 98, No. 6, December 1990, by Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler.
  3. “The Power of Touch: An Examination of the Effect of Duration of Physical Contact on the Valuation of Objects”, Judgment and Decision Making, Vol. 3, No. 6, August 2008, pp. 476-482, by James R. Wolf, Hal R. Arkes and Waleed A. Muhanna.
  4. “Law, Biology, and Property: A New Theory of the Endowment Effect”, William and Mary Law Review, Vol. 49 No. 6, 2008, by Owen D. Jones and Sarah F. Brosnan.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Motivated Reasoning

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Behavioral Matters: Insights from the application of Behavioral Finance | Issue 11

Written by Michael A. Ervolini

8 min read

Motivated Reasoning

“Whenever a new observation or thought came across me, which was opposed to my general results, [I tried] to make a memorandum of it without fail and at once; for I had found by experience that such facts and thoughts were far more apt to escape from the memory than favorable ones.”

– Charles Darwin

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INTRODUCTION

Confronting our own mistakes in judgment is painful. It is one reason we rationalize. Rationalization can, however, alter our interpretation of facts and lead to ineffective decisions. Rationalization is one of the powerful unconscious forces that can drive you towards behavioral investing. In this essay we discuss rationalization, motivated reasoning and five simple ideas for greater self-awareness.

WISHFUL THINKING

Rationalization is something we all do. Call it wishful thinking. By either name, it’s the tendency people have to fit perceptions of reality into a mold that is heavily influenced by preferences. Most of us are highly selective in the information we choose to process and how we process it, for emotional rather than analytic reasons.

When it comes to equity investing, wishful thinking can be devastating. It can blind us to undesirable facts without which we are likely to make ineffective decisions. Rationalizing causes us to depend on confirming information and minimize the significance of conflicting information. Since rationalizations come about comfortably and naturally, they often hide from our conscious ability to detect them, let alone manage them.

MOTIVATION MATTERS

One model for understanding how and why we rationalize, called Motivated Reasoning, suggests that the brain works to satisfy two distinct functions simultaneously – analytic thinking and emotional thinking. While analytic thinking strives to achieve the best fit for the data at hand (accuracy), emotional thinking wants to reinforce existing beliefs and diminish conflicting data (directional).

Those directional goals reflect our beliefs, biases and desires. Interplay between accuracy and directional goals can result in radically different reasoning given the same information at different times. Or as Professor Ziva Kunda puts it: “People rely on cognitive processes and representations to arrive at their desired conclusions, but motivation plays a role in determining which of these will be used on a given occasion.”

NOBODY’S FOOL

Rationalization is often misconstrued as an intentional effort to fool ourselves. To the contrary, we are often very sincere in our assessment of our reasons, while rationalizing. Consider the commonly observed behavior from Prospect Theory involving “risk seeking with losses.” A new position is down by 30% a short time after purchase. The manager decides to buy more believing that it is at a bargain price and sure to bounce. Objectively this may represent a shrewd capitalization on an over-beaten stock. On the other hand, it might be another case of taking even greater risks in the hope of ultimately breaking even.

The interaction between facts and unconscious desires is explained by Professor Kunda this way: “People do not seem to be at liberty to conclude whatever they want to conclude merely because they want to. They draw the desired conclusion only if they can muster up the evidence necessary to support it.“

A contributing factor is that we have a strong need to explain why we make our decisions and actions to ourselves and to others. In explaining our reasoning, motivations for self-efficacy and respect, result in our formulating a narrative. The narrative lays out all the facts as a reasonable and compelling story. Our need to feel good about ourselves and be respected by others, however, fills in around the facts until the narrative morphs into more of a fable than an accounting of what transpired.

RATIONALIZING BEHAVIOR

Rationalization underpins many well known behavioral tendencies: Self Attribution, Anchoring, Hindsight Bias, Optimism Bias and overconfidence, to name a few.

Motivated Reasoning can result in our need for a certain conclusion that then shapes how facts are interpreted. The need to explain can lead to narratives that deliver the wrong lessons to our memories. This, in turn, can result in heuristics, beliefs and biases that push us repeatedly and predictably towards ineffective decisions. Or as Artimus Ward once said: “It ain’t so much the things you don’t know that get you in trouble. It’s the things you know that just ain’t so.”

CONCLUSION

Rationalization reflects an internal struggle between interpreting facts and wanting an outcome that coincides with a belief or desire. As a result, the brain converges on a solution that incorporates available information while minimizing negative and maximizing positive feelings.

Rationalization positions us to readily accept facts that support our desire or belief while urging us to hold unfamiliar or unpleasant facts to a higher standard. Unconscious filtering results in a narrative that passes both our conscious scrutiny and that of others whose respect is desired. Ironically, scrutinization of why decisions were made or actions taken actually gives the illusion of being objective. To make matters even more difficult, the more intelligent the person is the better they will be at constructing and presenting a believable narrative.

Tough-minded investment management requires strong doses of introspection. To help in implementing your heightened self-awareness here are five reminders to pin up on your office wall:

  1. The brain tries to see relationships or stories, even when there are none.
  2. The brain forgets and remembers what it wants, in a very biased way.
  3. Narratives, even the most earnest of them, reflect Motivated Reasoning.
  4. Actively search for data that was overlooked or contradicts my theories or beliefs.
  5. How would someone who disagrees with me look at this data?

ENDNOTES

  1. “The Case for Motivated Reasoning”, Psychological Bulletin, the American Psychological Association, November 1990 Vol. 108, No. 3, by Ziva Kunda.
  2. Perspectives on Self-Deception, by Brian P. McLaughlin and Amélie Oksenberg, University of California Press, 1988.
  3. How We Know What Isn’t So: The Fallibility of Human Reason in Everyday Life, by Thomas Gilovich, Simon & Schuster, 1993.
  4. Don’t Believe Everything You Think: The 6 Basic Mistakes We Make in Thinking, by Thomas E. Kida, Prometheus Books 2006.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Thesis, Narrative, or Just Another Disappointing Story

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Behavioral Matters: Insights from the application of Behavioral Finance | Issue 9

Written by Michael A. Ervolini

8 min read

Thesis, Narrative, or Just Another Disappointing Story

“What is most important is not dispelling particular erroneous beliefs, but creating an understanding of how we form erroneous beliefs.”

– Thomas Gilovich

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INTRODUCTION

Stocks are often managed on the basis of a thesis. This has come to mean that the manager has a clear expectation of how a stock will add alpha to the portfolio and she can express it in a tight sentence or two. The mere existence of a thesis suggests purpose, conviction and discipline. On the other hand, the dictionary defines thesis as an unproved statement or argument put forward as a premise. Too often the tentative nature of a stock’s thesis is lost, inviting behaviorally motivated decisions that undermine performance. In this essay we examine the nature of the investment thesis and how, lacking sufficient self-awareness, it can be just another disappointing story.

MIND YOUR THESIS

Our unconscious brain plays a dominant role in the decisions we make. Many scientists now believe that the role of our conscious brain, to a large extent, is to create a narrative so that we can understand what our unconscious brain has already decided.

A thesis can, therefore, as easily be the end result of intense research and process or the verbal expression of one or more instinctive judgments. Consequently, the thesis for stock A may be fact based and built entirely from your process while the thesis for stock B might feel comparably formulated but reflect much less discipline. Understanding the veracity of each thesis in your portfolio can help you strengthen your process and improve performance.

SELLING YOUR THESIS

Buying stocks often is a highly disciplined and process driven activity. Not so with selling. Rigorous investigation points to selling as being underdeveloped with regards to research, analysts’ recommendations, capital expenditure and overall industry investment. The short shrift being given to selling, suggested by these signs of inattention, is underscored by the uneasiness exhibited as most managers explain that they are not as confident in their sells as their buys.

Selling is, therefore, more judgmental and thus prone to behavioral influences. One way this can be observed is through thesis drift. For example, a stock might initially be purchased based upon growth at a reasonable price (GARP) but as the price continues to fall it is reclassified and held as a value stock. This change in thesis might in fact be a case of nimble and responsive portfolio management or just another instance of the Disposition Effect.

The Disposition Effect is perhaps the most studied behavior affecting professional equity managers. It states that when choosing positions in the portfolio to sell managers are behaviorally more inclined to sell winners over losers. This behavior can lead to a relatively high turnover of gains in the portfolio and a commensurate longer holding period for losers. Redefining the thesis for a stock, as in the example above, can reflect the unconscious desire to avoid realizing a loss and formulating a narrative to help make that happen.

PAINFUL AVOIDANCE

Thesis drift can also result from cognitive dissonance. A term coined by the social psychologist Leon Festinger in the 1950’s, cognitive dissonance refers to the discomfort we feel when holding on to mutually inconsistent beliefs. In finance, cognitive dissonance commonly involves our sense of self efficacy. We are, after all, smart, trained and capable investors yet we often find ourselves owning a notorious loser. Our unconscious wants desperately for us to feel capable yet there is the not so small matter of this unfortunate position stinking up the portfolio. How we manage this dilemma can impact performance both today and tomorrow.

The self-aware professional confronts such situations by examining his process. His goal is to learn, improve and reduce the chance that the same misadventure will occur again. Others might formulate a narrative for why riding this stock down to the bottom was a reasonable decision. In such instances the self protective mandate of our brain may be initiated before we have even had a moment to think about what happened consciously. Knowing that our unconscious can override introspection is knowledge that can help us learn from the decisions made in 2008 rather than put them behind us too quickly.

CONCLUSION

The thesis under which you hold a stock is only as good as the process under which it was developed. Self-aware investors with rigorous process can rely on thesis to guide as well as explain their buys. When it comes to selling, however, the lack of discipline and process make formulating a sound thesis more challenging. Learning to question the thesis of each position held as thoroughly as that of a new buy is how many managers are preparing for the rebound. The alternative may have you generating a narrative that your clients won’t be happy with.

ENDNOTES

  1. How We Know What Isn’t So: The Fallibility of Human Reason in Everyday Life, by Thomas Gilovich, 1993, Simon and Schuster.
  2. “The Origins of Cognitive Dissonance: Evidence from Children and Monkeys”, by Louisa C. Egan, Laurie R. Santos, and Paul Bloom, Psychological Science, November, 2007.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.

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Stressing Performance

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Behavioral Matters: Insights from the application of Behavioral Finance | Issue 8

Written by Michael A. Ervolini

8 min read

Stressing Performance

“Nothing is more difficult, and therefore more precious, than to be able to decide.”

– Napoleon Bonaparte

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INTRODUCTION

No one has to tell you what stress feels like. It is your job to make the tough decisions about which names stay in the portfolio and which go. A burdensome responsibility, even in the best of times. But these are not the best of times. Your normal processes are being wracked by a market slump well outside your career experience combined with outflows that can be unnerving. If you are sensing in yourself a few raw nerve endings, that is only natural. It is one thing to survive stressful times – quite another to excel during them – ask any jet fighter pilot. In this essay we examine the nature of stress, its impact on critical thinking and what top professionals are doing to harness its effects rather than be overwhelmed by them.

FEELING IS BELIEVING

Stress isn’t always a bad thing. After all it is simply a state of heightened emotional and physiological awareness. Athletes, actors, public speakers and others use positive stress to strengthen their performance. Eustress, a term coined by researcher Richard Lazarus, is felt when the demands being placed upon us seem within our ability to handle. Coping with these stresses is exciting and actually heightens our abilities. In other words “getting pumped up” to perform involves harnessing positive stress.

Negative stress or distress, on the other hand, is felt when we are overwhelmed. Fears of failure or feeling out of control are powerful stressors that can severely limit our thinking and actions. During such experiences we are heavily driven by emotions that, while instinctive, are not the instincts that propel us to do our best. Learning what stresses you, and how to better manage these stressors, is all part of professional self awareness.

DR. JEKYLL, MR. HYDE

Stress can change who you are … or at least how you think. A diminished ability to consciously make good decisions is a common reaction to stress. Stress elicits our brain’s primitive protective responses, that old “fight or flight” feeling. These ancient instincts worked well when we needed protection from a marauding Woolly Mammoth, but are generally less helpful when managing modern sources of stress like market volatility or unhappy investors. This instinctive over-ride of conscious decision making limits us to only part of our brain, the part that doesn’t want to think. It prefers action.

Here are a few ways that stress can impede your decision-making.

Narrow framing: Distress causes us to curtail research and investigation prematurely. This rush to be done results in limiting the number of options we consider; emphasizing simplicity and expediency.

Shortened time horizon: Negative stress can push us towards a quick fix, even when that fix may cost us in the future. We just want the pain to stop.

Heuristics: Stress can result in an over reliance on simple rules-of-thumb. When succumbing to the desire to “do something” we might repeatedly apply ineffective solutions rather than reassess.

Negativity: Stressors can weaken our self confidence, lower our creativity and tilt our viewpoint so that more alternatives seem to possess negative outcomes. This “glass mostly empty” approach to decision making often becomes self fulfilling.

STRESS THIS

So how can you benefit from the current market chaos? We recommend building upon your self awareness, discipline and process. In general, good coping skills help us negotiate stressful times. They enable us to increase our sense of self-efficacy and perception of control. According to Dr. Albert Bandura self-efficacy is our sense of competence, our belief in our own abilities. The more capable we feel in any given situation, the less distress. Our sense of control also helps determine if we experience eustress or distress. According to Harry Mills, Ph.D “The perception of being in control (rather than the reality of being in or out of control) is an important buffer of negative stress”. Our sense of competency and control, therefore, act together in determining our personal reactions to stressors.

Self awareness, discipline and process are the tools you possess to strengthen your feelings of self-efficacy and control. The more you understand and believe in what you do at each decision point, the better you can manage stressors. As you learn to harness stress the more your portfolio decisions will reflect your strategy and analytic thinking rather than those unexamined rules-of-thumb hiding in your unconscious.

CONCLUSION

Stress is part of life. Minimizing negative stress is a skill that can be developed. The further you develop self awareness, discipline and process the better you will handle stress and the better the decisions you will be placing in your portfolio.

Managing stress and thinking clearly as markets gyrate around you can have an obvious impact on return. They can also mean the difference between having your portfolio, strategy and processes well positioned for the eventual market rebound or being caught flat-footed while others garner assets.

ENDNOTES

  1. “Judgment and Decision Making Under Stress: An Overview For Emergency Managers”, Journal of Emergency Management, 2008, by Kathleen M. Kowalski-Trakofler.
  2. Making Decisions Under Stress: Implications for Individual and Team Training, American Psychological Association, 2000, edited By Janis A. Cannon-Bowers and Eduardo Salas.
  3. Sitting in the Hot Seat: Leaders and teams for Critical Incident Management, John Wiley & Sons, 1997, by Rhona Flin.
  4. Sources of Power: How People Make Decisions, MIT Press, 1998, by Gary Klein.

MICHAEL A. ERVOLINI, AUTHOR

The ideas expressed on this website are developed and/or curated by Michael Ervolini. Mike has spent his entire 35 year + career leading efforts to improve and strengthen active management.