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Implementing Behavioral Portfolio Management

April 30th, 2013

by C. Thomas Howard, PhD

Advisor Perspectives welcomes guest contributions. The views presented here do not necessarily represent those of Advisor Perspectives.

Behavioral portfolio management (BPM) is based on two categories of financial market participants: emotional crowds and behavioral-data investors (BDIs). Emotional crowds are investors who base decisions on anecdotal evidence and emotional reactions to unfolding events. Human evolution hardwires us for short-term loss aversion and social validation, which are the underlying drivers of emotional crowds. On the other hand, BDIs thoroughly and extensively analyze behaviorally-driven price distortions and build portfolios based on these distortions.

Four weeks ago, I introduced the concept of behavioral portfolio management (BPM) as a way to build superior portfolios. Three weeks ago, I discussed the first basic principle underlying BPM: Emotional crowds dominate market pricing and volatility. The next week, I presented the second basic principle: Behavioral-data investors can earn excess returns. Last week, I introduced the third and final basic principle: Investment risk is the chance of underperformance.

In this final installment of my five-part series, I show how advisors and investors can implement a BPM-based strategy.

Implementing BPM

There are three key steps to implementing BPM: redirectingyour emotions, harnessing market emotions and mitigating the damage of client emotions on their portfolios. The first and third steps must be accomplished in order to successfully implement the second step. Many investment firms provide excellent materials to aid advisors in helping clients avoid emotional errors and improve the investment decision process.

But beyond an inventory of common emotional mistakes and antidotes, not much is available regarding how to harness market emotions. This is an important omission. Emotion-harnessing portfolios are key to earning superior returns. This article illustrates how to create them.

BPM-based asset allocation and portfolio construction

The standard approach to portfolio construction is to maximize return for a given level of volatility. This is often referred to as a risk-return analysis. In last week’s article, I argued that the typical measure of risk – volatility – is really a measure of emotion. So risk-return analyses are really emotion-return analyses. To avoid placing emotionally charged volatility at the center of asset allocation, we need to sideline it to the greatest extent possible.

BPM-based asset allocation uses a personal endowment approach to portfolio construction, a topic addressed in a recent article. Endowments are faced with the dual charge of providing an annual income stream to a university or other institution as well as growing the portfolio over a long-term horizon. To a large extent, endowment managers are insulated from the short-term performance pressures facing many other investment managers. For this reason, they are able to construct the best portfolios for meeting the dual charge of regular income and long-term growth.

Endowment fund behavior provides the basis for BPM-based asset allocation.

The first step is to divide the client portfolio into three buckets: short-term income and liquidity, capital growth, and alternatives. The short-term bucket is invested in low- or no-volatility securities that are sufficient to meet the client’s short-term needs with virtual certainty. This removes volatility from conversations regarding this bucket.

The capital growth bucket is built to maximize long-term wealth. Since the investment horizon is long for this bucket, the focus should be on expected and excess returns. Endowment funds do exactly this by overweighting the asset classes with the highest expected returns. Endowments heavily weight equities, with very little invested in bonds.

A significant challenge facing advisors is that clients have difficulty thinking long-term, as they are hardwired for short-term loss aversion. Instead of a 30-year horizon, for example, they see a series of 30 one-year time frames or a series of 120 one-quarter time frames. In each period, they apply short-term loss-aversion criteria. Some clients have difficultly staying the course with high-return, volatile investments such as stocks. Short-term loss aversion can undermine capital growth portfolio performance, as clients can make decisions based on current market volatility.

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