Identifying Biases in Asset Management Decisions

Biases are systematic patterns of deviation from rationality. Armed with insights from the fields of behavioural economics and cognitive psychology, many businesses - including asset management companies - are trying to debias their decision-making strategies. Aiming to improve business decisions, asset managers can hope to improve stock selection, volumes and portfolio shares as well as purchase and selling points. Even under conservative assumptions, McKinsey claims in An analytics approach to debiasing asset-management decisions that identifying common biases and introducing strategies to counter them can improve fund performance by 100 to 300 basis points.

To identify biases in fund managers and management teams, McKinsey proposes an analytic model based on decomposition analysis. An analytical model can use historical data of fund performance and investment decisions, as well as the processes used by funds managers and teams to decompose the fund’s performance in three categories: security selection, weighting and exit. Depending on which activity adds performance and which reduces it, priorities can the be given to tackling biases related to that specific activity. For example, lacking performance when selling stock may be a result of selling stocks too early due to the wish to maintain profits made and not to lose them again.

To tackle such biases, McKinsey proposes different tools including checklists, devil’s advocate, premortem, red team - blue team or visual nudging. Using these to improve investment decision making, asset managers can improve the value of their services to investors and especially against passive products, claims the consultancy.