By Dean Mcintyre, Factset
t should be easy to identify good active fund managers. They beat their benchmark with consistency, and their stock decisions appear to add value over time. Or at least that’s the theory.
In practice, however, it can be difficult to distinguish skill from luck and to measure the impact of behavior on performance.
Behavior of Influence
Fund managers are subject to all sorts of behavioral biases that influence their decision making and affect the returns they generate for investors. Whether it’s an instinct to follow the herd or a tendency to “anchor” to previous price points, behavioral biases make a real difference.
Yet standard attribution analysis (the blunt instrument that it is) may not capture such influences. Attribution is often black and white, so key questions may remain unanswered, such as:
- Is a fund manager really adding value? More importantly, where and how is this attributed?
- Have they just been lucky with one or two holdings?
- Has their performance come from active behavioral decisions or simply being in the right place at the right time
Thankfully, our ability to quantify fund manager decision making has improved greatly in recent years.
Deeper Dives
Behavioral finance was a recognized subject in the 1970s and 1980s, thanks to the work of academics such as Amos Tversky, Daniel Kahneman, and many others. It really came into the spotlight, however, following the financial crisis. Techniques for measuring the behavioral influence on fund performance are becoming more sophisticated, as the science of behavioral finance is better understood and more widely employed by fund management groups.
For example, these techniques can recognize that fund managers may have a tendency to “fall in love” with their best ideas so the speed and skills with which they sell stocks can be interrogated. A manager’s tendency to herd with other investors at times of market turmoil can also be measured.
It is possible to look at whether a manager’s size bias has added value and also whether this is an active decision that has changed over time or a structural position that the manager has simply been lucky with. It is also possible to strip out the sizing bias altogether to see whether a fund manager’s stock decisions have added value.
Improvements in this area are being made all the time. For example, we can now create a synthetic version of a fund manager’s portfolio and look at the difference between that and his actual portfolio. This can expose a fund manager’s biases and/or skills. For example, is he too slow to sell or too early to buy?
The tools available to performance analysts are developing all the time, building on metrics such as hit rates, active share, plus upside/downside capture.
Why It Matters
Why is it important to understand these traits? Increasingly, fund managers are mandated to manage a fund in a particular way. Asset allocators will generally have bought into the fund because they want exposure to a particular style. If a manager strays off piste, it will skew her risk measurements.
Insight into behavioral influence may also help fund managers shape mandates for better performance. For example, if a fund is mandated to have very low turnover, it is possible to examine whether that decision is adding value.
It is also possible for fund managers to identify whether performance is impaired because they aren’t able to sell underperforming shares quickly enough. This would give them a basis from which to improve the parameters of their mandate and, therefore, deliver better performance.
