A predictable world doesn’t exist. Enter heuristics: a method whereby people deliberately ignore some available information in order to make quicker decisions. Most people and organizations—even traders—rely on heuristics.
Investing doesn’t always require complex solutions. Instead, try these two types of heuristics: recognition and equality.
Recognition heuristics occur when people choose the option they recognize most—so an investor choosing between a known or unknown stock would pick the one that’s more familiar. Recognition-based portfolios, on average, outperform the market, managed funds, and randomly chosen portfolios.
Used in concert with recognition, equality heuristics also have a lot of potential for investors. Using this method, all known alternatives are treated equally to make a decision. An investor with a pool of 100 stocks he recognizes would allocate cash equally among them.
Our research shows the more stocks in which you are investing, the more likely equality heuristics are to outperform more complex processes, such as the mean-variance method.
That happens because mean variance requires investors to understand each stock’s performance history, estimate all known parameters, and then make predictions. That’s possible in a controlled environment. But the more stocks you look at, the more likely you are to choose the wrong parameters, make more errors, and generate less return.
Equality heuristics, by contrast, are more intuitive. Investors don’t need knowledge of historical performance or to understand every available stock. So equality heuristics have the potential to be more robust and useful than statistics in real-world conditions.
To apply heuristics, advisors could look at their clients’ own stock preferences. Stocks your clients may have read about in the paper or heard about from friends could be a legitimate match for their portfolios.