Let go of ‘recency bias’ in your next investment decisions

Many find it easy to recall recent events or the last thing said at the end of a meeting – an outcome psychologists call the ‘recency bias’. It is much harder to recall events that occurred further back in time, or in the middle of a particularly long meeting, unless one took the effort to take notes and commit key points to long-term memory.

For financial market investors, this can be a particularly troubling bias. One that can work against us in making good investment decisions. Today, for example, many of my own conversations with colleagues and clients are focused on the first-half of the year and whether the gloom we experienced in the form of a correlated fall in both equities and bonds is likely to continue for the foreseeable future.

Many have asked the question about whether one should just ‘wait out’ this uncertainty in the supposed safety of cash – an approach that history would caution against as it can significantly hurt long-term returns as well as the preservation of wealth, especially during times of high inflation.

This approach is, however, a reflection of recency bias. It is possible, of course, that recent market trends could continue for a while longer – some have made that case based on an assessment of macroeconomic data today. However, history shows us that a continuation of the current slump would be an exceedingly rare event.

Several investor surveys in recent weeks have shown sentiment and positioning is already exceedingly bearish. If anything, this makes a continuation of H1-2022 market trends less likely. What is important, in our view, is to step back and make a fresh assessment based on economic and market data today, as opposed to falling prey to the bias where we assume recent financial market trends would simply extend, since the latter can ultimately hurt long-term returns.

The following example may help clarify the recency bias that cloud most investors’ judgement. A 2008 study found that insurance demand tended to rise after the occurrence of a natural disaster. A statistician looking at historical data would argue that the chances of a specific natural disaster, for example, does not rise just because someone has just experienced such an event.

In this case, individuals would be better off purchasing insurance at any given time (ideally before, rather than after, a natural disaster) rather than rushing to do so in the immediate aftermath of a disaster – the classic recency bias at play.