THE DANGERS OF MECHANICAL INVESTMENT DECISION-MAKING: THE CASE OF HEDGE FUNDS

Abstract

Over the last 20 years, investors have come to approach investment decision-making in an increasingly mechanical manner. Optimizers are filled up with historical return data and the “optimal” portfolio follows almost automatically. In this paper, we argue that such an approach can be extremely dangerous, especially when alternative investments such as hedge funds are involved. Proper hedge fund investing requires a much more elaborate approach to investment decision-making than currently in use by most investors. The available data on hedge funds should not be taken at face value, but should first be corrected for various types of biases and autocorrelation. Tools like mean–variance analysis and the Sharpe ratio that many investors have become accustomed to over the years are no longer appropriate when hedge funds are involved as they concentrate on the good part while completely skipping over the bad part of the hedge fund story. Investors also have to find a way to figure in the long lock-up and advance notice periods, which makes hedge fund investments highly illiquid. In addition, investors will have to give weight to the fact that without more insight in the way in which hedge funds generate their returns it is very hard to say something sensible about hedge funds' future longer-run performance. The tools to accomplish this formally are not all there yet, meaning that more than ever investors will have to rely on common sense and doing their homework.