A portfolio manager’s job is to make decisions. All day, every day. Some of these decisions lead to deals, but many do not. Therefore, the key question for portfolio managers is which decisions are helping performance and which are hurting performance.What types of decisions are they good at making, and which are they better suited for someone, or something else, to make? Could I use my energy more efficiently? Input Attribution of decisions Analytics is the largest and most important area of behavioral analysis for investors.
Until recently, these questions were almost impossible to answer. A primary evaluation tool for many investors and fund managers, best performance attribution analysis works backwards by starting with a result and comparing it to the performance of alternative indices. But it doesn’t help much for managers. While useful in explaining why a portfolio performed well in a particular time period, this analysis cannot identify what a fund manager could do differently to achieve better results. .
Decision attribution analysis has become significantly more sophisticated in recent years with the exponential growth of machine learning capabilities. Decision attribution is a bottom-up approach compared to the top-down approach offered by performance attribution analysis. Examine the actual individual decisions made by managers during the period analyzed and the circumstances surrounding those decisions. Evaluate the value those decisions created or destroyed and identify evidence of their skill or bias.
Sure, managers make different decisions in different market environments, but that’s not all. Fund managers, of course, select different stocks at different points in the economic cycle. However, the selection decision is only one of the many selections the fund’s manager makes during the life of the position. There are also decisions about when to enter, how quickly to adjust size, how big, and whether to add and subtract positions over time. Finally, the manager decides when to withdraw and how quickly.
These decisions are less visible and less analyzed. Having studied the behavior of his manager in stock portfolios for nearly a decade, what evidence do I have that while changing picking behavior in response to changing market conditions, the rest of the ‘movements’ are more habitual and consistent? I have seen it many times.
Anyone who has a history of daily holding data for a portfolio has the raw materials needed to see where their skills as an investment decision maker lie and where they consistently make errors. I don’t want to invite , but decision attribution is a complicated task. Any investor who has tried to do it can attest to it. Interesting as a one-time exercise, it’s only really useful if you can do it on an ongoing basis. Otherwise, how can you tell if your skills (not just luck) are improving?
Only recently has technology enabled us to perform deterministic attribution analysis on an ongoing basis in a reliable manner. This is especially useful in a market like the one we’re in right now. Not only does it help managers understand what they can do to get better performance results, but it also helps them prove their skills to investors when performance is negative.
No one is a perfect decision maker. Sophisticated allocators of capital have no illusions about it. But if, as his portfolio manager, he can show his investors with data-driven evidence, he can show them that they know exactly what they’re good at and the steps they’re taking to improve. It helps a lot if you can. And given the availability of the underlying data and current analytical toolsets, there is no valid excuse not to do so.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, and the opinions expressed do not necessarily reflect those of CFA Institute or the author’s employer.
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Claire Flynn Levy
