It’s well known in behavioral finance that investors experience a loss 2-3x more intensely than a gain of the same magnitude. This loss aversion leads investors to avoid even rational bets, according to a Reuters story on a recent study by a Cal Tech scientist.
Laboratory and field evidence suggests that people often avoid risks with losses even when they might earn a substantially larger gain, a behavioral preference termed ‘loss aversion’,” they wrote.
For instance, people will avoid gambles in which they are equally likely to either lose $10 or win $15, even though the expected value of the gamble is positive ($2.50).
The study indicates that people show fear at even the prospect of a loss. Markets are designed to generate fear, not to mention all of the bearish commentators on CNBC. Fear leads to poor decisions, like selling near the bottom of a correction. Unless you are planning to electrically lesion your amygdala, the fear is going to be there–so what’s the best way to deal with it?
The course we have chosen is to make our investment models systematic. That means the decisions are rules-based, not subject to whatever fear the portfolio managers may be experiencing at any given time. Once in a blue moon, excessive caution pays off, but studies suggest that more errors are made being excessively cautious than overly aggressive. A rules-based method treats risk in a even-handed, mathematical way. In other words, take risks that historically are likely to pay off, and keep taking them regardless of your emotional state. Given enough time, the math is likely to swing things in your favor.
—-this article originally appeared 2/10/2010. In the two years since this was written, investors have continued to pay a high price for their fear as the market has continued to advance. There are always scary things around the corner, but a rules-based process can often help you navigate through them. Investors seem to have a hard time learning that scary things don’t necessarily cause markets to perform poorly. In fact, the opposite is often true.