Recency Bias Linked With Other Pitfalls

This month's article is the ninth in a series called "Managing Behavior in a Volatile Market" and Part II of a discussion on recency bias. This series provides data and insight into the identification of key behavioral biases and also shows how to manage client behavior and emotion in this highly volatile market environment.

A substantial part of this series will be a review and analysis of answers to behavioral questions that were completed by a diverse set of 178 individual investors in 2011. The investors polled were not subscribers to Morningstar.com and/or Morningstar investor newsletter publications like the last survey, but they fit a similar profile in terms of investment objective and investor description.

By way of background, the survey questions were written to identify 20 key behavioral biases that I outline in my book, Behavioral Finance and Wealth Management. The second edition of the book, with updated biases and new case studies, just hit the cyber-market.

As noted in earlier articles, the intent of the survey was twofold. First, I wanted to identify the most prevalent biases ("Primary Biases"), so advisors would know what to look for when working with their clients. Second, I wanted to identify what secondary behaviors ("Secondary Biases") might also be lurking behind these primary biases. In other words, if client Smith has easily recognizable bias X, what other of the 19 biases might client Smith also be subject to?

The purpose in doing this is that advisors can hopefully recognize not only primary biases, but secondary biases as well. Often it is the unrecognizable biases that can cause substantial harm when attempting to keep clients on track to attaining financial goals. Advisors can hopefully gain significant insight into a range of a client's behavioral tendencies simply by being aware of a single common bias.

In order to rank as a primary bias, 50% or more of respondents need to answer at least "Agree" or "Strongly Agree" to a question designed to identify a certain bias.

There were seven biases that garnered at least 50% positive responses:

Loss Aversion Bias: The pain of losses is greater than the pleasure of gains