The author contends that traditional investment planning fails to recognize
investors' behavioral preferences and biases, resulting in suboptimal
performance. He proposes to integrate behavioral finance into the investment
process by recasting risk–reward measures into a framework based on the
investor's goals.
The recent bear market reinforced the value of diversification and modern portfolio
theory. Behavioral preferences and biases, however, prevented many investors from
enjoying those benefits. Rather than simply relying on traditional measures of
annualized return and standard deviation, the author advises recasting such information
in terms of meeting or failing to meet investor goals over the investment horizon. Such
a custom approach, although more complex, should clarify risk exposure and boost
investors' confidence. The author outlines the strengths and shortcomings of traditional
measures and explains how to reconcile them with a goals-based approach.
Traditional risk measures do not fully capture market behavior and are of limited
relevance to investors. Standard deviation assumes a normally distributed return pattern
despite ample evidence of skewness, kurtosis, and heteroscedasticity. Behavioral finance
also shows that investors are not risk averse but loss averse, suggesting measures based
on the likelihood of loss, severity of loss (downside deviation—Nawrocki,
Furthermore, expressing risk measures in terms of time intervals does not capture
investor risk exposure to successive losses or to risks that come and go before the end
of the period. The author advocates measuring risk as violating investor preferences or
goals without specifying a time period. Although these measures are more difficult to
calculate than such statistical measures as standard deviation, they can be based on
Monte Carlo simulations and should be better aligned with the way investors perceive
risk.
The traditional approach to risk profiling can be misleading. Interviews and
questionnaires have been shown to have limited accuracy. But even accurate risk
tolerance measures can lead to poor strategy implementation. A risk-tolerant investor
does not need to hold a risky portfolio if a conservative portfolio will achieve his or
her goals, nor is there merit in a conservative strategy that is unlikely to meet the
investor's return objectives, even if the investor is risk averse. Furthermore,
investors tend to have different risk tolerances for different objectives. Such mental
accounting is difficult to incorporate into the traditional overall framework, which
requires a single, overall risk tolerance. The alternative is to develop multiple
strategies that can then be integrated into an overall portfolio by the advisor.
In addition to investor preferences, such as mental accounting and loss aversion,
behavioral finance identifies investor biases, such as overconfidence, hindsight bias,
overreaction, belief perseverance, and regret avoidance. The author contends that a
goals-oriented approach helps investors avoid such biases.
A fully customized goals-based approach is complex, but strategies could be built around
common goals, such as college saving, by simply pulling together investor-appropriate
strategies. The author illustrates goals-based strategies for investing to meet
lifestyle needs and for investing for a fixed horizon that can be modeled as an
efficient frontier.
To plan for lifestyle needs, the author recommends defining reward as the expected
sustainable spending rate of a given strategy and defining risk as the minimum
sustainable spending rate. Risk and reward are then measured over the entire horizon
rather than annualized. The author points out that institutional investors have long
used asset/liability models to assess the implications of strategies and suggests that
individual investors who tend to be less familiar with theory and statistics would
likely benefit from such analysis. Furthermore, the practitioner can align the results
with traditional investment strategy because expected spending is derived from expected
return and the minimum spending rate is derived from downside risk. The process would
likely result in portfolios managed in absolute—rather than relative—terms.
To invest for a fixed horizon, the author suggests using expected portfolio value as the
reward measure. Risk can be measured as the potential for loss or as the worst-likely
portfolio value. In addition, the risk-free investment is defined as a zero-coupon
Treasury maturing at the investment horizon. In conjunction with the risk-free asset,
the remaining assets could be managed aggressively for return while assuring the minimum
acceptable outcome. The practitioner must then determine whether such a portfolio may be
too conservative, whether the horizon may change (rendering the zero risky), whether the
return on the zero is sufficient, and whether the investor can tolerate interim
volatility of the zero despite its ultimate certain value.
The author concludes that incorporating goals-based investing improves traditional
investing in terms of measuring risk, profiling risk, and managing behavioral biases. At
the same time, goals-based investing integrates the findings of behavioral finance
within the context of portfolio theory.