They would ride out both bear and bull markets with a cool head and understand that it is next to impossible to time the swings successfully.

Ah, the ideal. If only the human brain worked that way. As a relatively young field of science, behavioral finance, has uncovered, individual investors are influenced by a smorgasbord of factors compelling them to behave irrationally where their portfolios are concerned. Though each investor is part rational economist, he is also part financial Neanderthal, motivated by a more primitive drive to survive. As financial strategist and economist James Montier laments, we are “part man, part monkey” when it comes to capital investment: overly confident and overly optimistic, we believe we can forecast presciently, attributing mistakes to bad luck and so failing to learn from them. The human brain, in a constant struggle between greed and fear – between the pursuit of reward and the desire to prevent loss – fells itself. These “anomalies” in investment decision making are actually the norm and lead to consistent inefficiencies in the overall markets.

Thankfully, a biT OF INSIGHT can go a long way. One of the advantages of studying behavioral finance is that the more investors are aware of their own irrational behavior, the more likely they are to optimize their own decisions. By taking a more structured approach to investing – using rational models and rules that keep those primitive reactionary tendencies in check – they effectively outsmart themselves. Life cycle models of asset allocation replace most decision making by calculating asset allocation and timing based on very specific criteria: investors following this model can presumably take a more hands-off approach to portfolio management. They might also manage to resist the urge to pull all their money out of equities when the market swoons. “It takes the emotion out of it,” says Wolfgang Mader, vice president at risklab, an Allianz Global Investors subsidiary.

Mader and his team are developing life cycle models that take this structured approach further by tailoring it to an investor’s profile to achieve an optimal asset allocation. This life cycle model is designed to take into account the full arc of an individual investor’s life, including age, expectations of income and growth rates, desired accumulation, bequest motives (or what the investor desires to pass along to heirs), and other life cycle details.

While typical retirement planning tools tend to stop at basic criteria like years to retirement and professed risk tolerance, the model includes additional personal details around wealth that can significantly impact the level of risk tolerance. Therefore, financial wealth and human capital are taken into account when it comes to deriving an optimal asset allocation. Level of education and employment sector, for example, can contribute to an individual’s overall wealth in terms of human capital: someone with a higher level of education can assume a higher expected income growth rate over his or her lifetime than someone without.

Likewise, a public servant may have a more reliable lifetime income stream than does an employee in the construction industry. “And if you are working in asset management and your income stream has a high correlation to the equity markets, you need to include this in your modeling process because there will be an interaction between your return and the risk attached to your income,” says Mader. In this case, your income would be considered more volatile, so you would reduce the amount invested in riskier assets.

By considering the relative riskiness of labor income, or human capital, this model offers investors a more tailored, and more optimal, allocation that will carry them through their entire life span. For example, conventional wisdom calls for reducing riskier assets post-retirement and moving them into fixed income to avoid unnecessary risk at that late stage. But your human capital is actually less reliable during your working life, since you may lose your job or your ability to work. As you move into retirement and begin receiving fixed, steady payments from your pension and defined contribution plans, the risk in your income actually decreases, says Mader. “You are then able to bear some more capital market risk. So it might be optimal to increase the allocation to assets with a higher risk profile again during retirement.”

And by increasing, rather than decreasing, one’s allocation to riskier assets in retirement, the investor solves another dilemma. Classic retirement planning tools only calculate up to that magical age of 65 and then focus almost solely on wealth preservation. “But you hope to have at least 20 years to go,” Mader notes. “If you have everything invested in cash, that is not optimal from a risk-return point of view. Having everything in a money market or risk-free investment doesn’t give you any risk premium.” The life cycle model offers an optimal allocation model up to the age of 120, even as it calculates the probability of one’s actually reaching that age based on mortality expectations. An individual investor could rerun the model for her or his accounts as often as necessary to make sure he or she has the optimal allocation for that period of time and set of life circumstances.

Mader and his team are currently working on building a life cycle model into retail funds. If used properly, the model has the potential to take the guesswork – and irrational impulses – out of investing for the long haul. “You want your savings to last a lifetime,” Mader says, adding that the goal of the life cycle model is to have a certain systematic exposure to assets with a higher risk-return profile. “Having this systematic approach helps give you control over these irrationalities.”

Published by PROJECT M in December 2008