Look Beyond Performance When Selecting Portfolio Managers

October 15, 2019

Why evaluating managers the right way can be complicated

You may have read some of Matt Potter’s posts before on Practically Speaking; he is becoming a regular contributor.  In today’s post, Matt shares some of his unique perspectives on investing. I love talking to Matt because he brings an interesting take to the table, as a CFA, a senior member of our Investment Services Team, and as a former employee of a New York based small cap money manager.  Please enjoy Matt’s post…  JDA

My passion for investing came somewhat later in life; I majored in psychology in college and never took any economics, finance, or accounting courses. I even went to graduate school with the intention of getting a PhD and becoming a university professor. Fortunately for academia, I realized that this would not be my ideal future path. My first job at a market research firm didn’t grab my interest, but the firm’s rollout of a 401(k) plan introduced me to investing -- and my future career.  

Fast forward a few years, and I entered an interesting phase of my career in which I worked closely with a number of different portfolio management teams. My role gave me an excellent opportunity to vicariously experience the successes and failures of several different investment teams and witness firsthand how they operated.

Identifying successful management teams

Portfolio management is more complicated and difficult than many outsiders (and advisors) believe, and so is the process of evaluating, hiring, and firing these managers. It’s possible to identify the more successful teams, but doing so requires a significant investment of time and effort, as well as an in-depth understanding of how solid teams operate and what ultimately drives their success.  Here’s what I learned in my years of working closely with portfolio managers:

  1. Investing is incredibly time- and labor-intensive. Managers typically review a company’s SEC filings in detail to understand the business model as well as the company’s opportunities and challenges. performance evaluationManagers also like to speak to or meet with company management. In addition to higher-level executives such as the CEO and CFO, managers may also interview people who are closer to the actual operations, such as division heads or regional managers. They usually also speak with equity analysts from other firms to understand the consensus view of a company, since most successful investments come from having a viewpoint that is meaningfully different from that of other investors. Good portfolio managers will search for details that others may overlook, such as flaws in analysts’ earnings models, underappreciated catalysts for improvement, etc. I was continually impressed with the amount of work managers would do to investigate a company before buying a single share.
  2. Hard work doesn’t guarantee investment success. While I do believe there is a correlation between a portfolio manager’s effort and results, even the most thorough analysis can miss something important. End markets evolve, competitive advantages can disappear, and nobody is immune from bad luck, such as a massive boiler malfunctioning at exactly the wrong time (real example). Even when the analysis and reasoning are sound, markets may not appreciate or value company developments as much as expected. Market sentiment matters, which can frustrate portfolio managers who “know” they are right about a company’s fundamentals -- but the market just doesn’t seem to care.
  3. All managers – even the most skilled ones – will have off years. There’s an old saying that “smart managers don’t get stupid overnight,” but it can still be surprising when a manager with a solid track record has an unexpected bad year or two.  This is not only normal, it should be expected. Manager alpha tends to be lumpy and unpredictable, and it’s certainly not unheard of for a “manager of the year” to wind up in the bottom quartile shortly after receiving industry accolades. A manager may be following the exact same process, with the exact same team, and yet see completely different outcomes from one year to the next. This is important to remember when evaluating a manager’s performance and deciding whether to fire or stick with them.
  4. Third-party consultants and prospective clients aren’t always good at evaluating manager performance. People often have trouble differentiating between true measures of manager performance and elements of the process that sound impressive in a pitch book but aren’t as impactful in practice. I tend to be wary of managers who believe they’ve discovered the optimal screening criteria or some other magic bullet, and have made that the cornerstone of their investment process. A narrative built around a single unifying investment principle and woven into a tight, methodical process can often wow an investment committee when it’s presented, but it might ultimately deliver less than it promises. I’ve heard some very compelling pitches associated with sub-par investment approaches.
  5. Portfolio management teams need humility and intellectual flexibility. Good managers adapt to changing circumstances. The real world is messy and unpredictable. Markets often behave irrationally, and stock prices frequently appear to fly in the face of common sense. Company fundamentals may or may not matter at any given time, and no investment approach works as consistently as its practitioners and clients would like. Investors who demonstrate hubris and stubbornness in the face of challenges or legitimate criticism also put me off. Yes, you need to have confidence in your skills and approach, but traits such as self-awareness and introspection serve managers well and are more important than the more performative and public relations qualities that sometimes characterize star managers.
  6. Data alone can’t effectively evaluate managers. While many of the criteria used to evaluate managers take the form of objective data (e.g., standard deviation, Sharpe ratios, and unnecessarily-complex words like kurtosis and heteroscedasticity), some of the most important factors are fuzzier and more difficult to measure. It takes time, effort, and access to judge a management team’s culture, as well as the quality of their decision-making process. Strengths aren’t always immediately apparent, and serious flaws might not show up until the market environment worsens. Luck can be mistaken for skill, and team members’ roles may be either more or less important than they appear on an org chart. Almost any portfolio manager can make a favorable impression during a brief well-scripted new business pitch. However, observing team members in their natural habitat as they interact and make investment decisions often yields much more valuable insights into the likely effectiveness of their process.
So you may ask, is this a pitch for a passive approach to investing?

No, I do believe that some teams are more skilled and more likely to achieve their performance objectives than others. In some ways, portfolio managers are a different breed from many other market participants.  They need a certain amount of confidence - bordering on arrogance - to presume that they can outperform other investors. At the same time, their performance is literally measured daily, so they experience constant pressure to produce strong returns (and anxiety about possibly being replaced if they don’t).  If you are willing to take the time and effort required to find superior managers, the results may be there.  If not, it makes sense to find someone (or a firm) that can.  

Legal Note

Investing involves risk including possible loss of principal. Alpha is the excess return relative to the return of the benchmark. Standard deviation is also known as historical volatility and is used as a gauge for the amount of expected volatility. Sharpe ratio is a measure of the return of an investment compared to its risk. Kurtosis is a statistical measure to describe the distribution by measuring extreme values in either tail. Heteroscedasticity is used to describe what happens when standard errors (the approximate volatility of the sample population) of a variable, monitored over a specific time frame, are not constant.

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