by Harold Evensky, CFP®, AIF®
Harold Evensky, CFP®, AIF®, is chairman of
Evensky & Katz in Coral Gables, Florida. He is an
internationally recognized speaker on investment and financial
planning issues and is the author of Wealth Management and
co-editor of The Investment Think Tank: Theory, Strategy, and
Practice for Advisers.
A year ago I asked, "Given the tumultuous markets for the last year
… why worry about research when the world is coming to an end?" My
answer was, "If the world does come to an end, it really won't
matter what we do with clients' investments; however, if it
doesn't, good planning has never been more important, given the
losses everyone has sustained."
Well, the good news is, the world didn't come to an end, but the
experience of the Great Recession certainly focused everyone's
attention on risk and asset allocation. The need for good planning
is unquestionably more important than ever. Nowhere have both the
need and possible solutions been addressed more rigorously than in
the professional journals. That focus is the theme for this
quarter's Investment Research column. Each of these papers presents
specific implementable ideas that will be considered by my firm's
investment committee. I hope you too will find bits and pieces that
allow you to improve your portfolio design and implementation
strategies.
"How to Kill a Black Swan," Remy Briand and David
Owyong, Journal of Indexes, July/August
2009, pp. 10–17.1 This is one of the
early papers to address this issue. As the authors note in the
introduction to this paper, "In our view, the events of last year
will force a number of changes in investment practices in the
following areas: management of extreme events … [and] strategic
asset allocation." They also remind us that extreme events,
characterized by volatility jumps, increased risk aversion,
negative returns for risky assets, and increased correlations
across asset classes, are not a new phenomenon, with 10 major
market events over the last 21 years, including Black Monday
(1987), the Mexican crisis (1994), the Asian crisis (1997), the
tech bubble (2000), and the more recent quant and credit crisis
(2007–2008).
The authors' primary conclusion is that an optimal solution for the
individual investor must incorporate worst case scenarios leading
to significantly smaller allocations to risky assets as individuals
approach retirement. Toward this end, they propose what they refer
to as risk-based asset allocations by expanding allocations to four
broad segments: equities, real assets, liability hedging, and
absolute return strategies. Their proposal for an expansion of the
traditional asset classes is a common theme in a number of the
following papers.
"Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes," Niels Bekkers, Ronald Doeswijk, and Trevin Lam, The Journal of Wealth Management, Winter 2009, pp. 61–77. This paper expands on the allocation concepts suggested by Briand and Owyong. In addition to stock, government bonds, and cash, the authors explore the efficacy of adding allocations to private equity, real estate, hedge funds, commodities, high yield, credits, and TIPs. After an extensive and very readable discussion of assumptions, process, and results, the paper concludes that mean-variance analysis "… suggests that real estate, commodities, and high yield add the greatest value to a traditional mix of stocks." As I found the assumptions reasonable (for example, a 0 percent risk premium and 26 percent volatility for commodities versus a 4.75 percent risk premium and 20 percent volatility for stock and a 3.75 percent risk premium and 16 percent volatility for real estate), their conclusions lead me to reconsider some of our firm's current allocations.
"Passive Versus Optimized Investing in Retirement Plan Portfolios," Jeff Grover and Angeline Lavin, The Journal of Wealth Management, Fall 2009, pp. 61–77. This paper offers an interesting and potentially implementable strategy for improving the risk/return characteristics of a portfolio allocated in accordance with a traditional Markowitz mean variance optimization. The basic premise is that complementing the traditional model (the passive portfolio) by incorporating William Sharpe's CAPM based single-index model (the optimized portfolio) will improve risk adjusted performance. Basically, the strategy modifies allocations by optimizing for "undervalued" funds where "undervaluation" is determined by the application of CAPM and measured by the Sharpe Ratio. The authors' premise is, "… if the Sharpe ratio can be used to identify low-risk and low-return funds, then a portfolio of these funds would likewise have the same characteristics of these individual funds." And it concludes, "… in the long run, the optimized strategy will provide the investor with equivalent cumulative returns and significantly lower risk. In addition, the optimized strategy reduces the number of funds and creates greater efficiency."
"The Myth of Diversification," David Chua, Mark Kritzman, and Sébastien Page, The Journal of Portfolio Management, Fall 2009, pp. 26–59. The fact that Mark Kritzman is one of the co-authors of this article would be reason enough to read it, and indeed you will be well rewarded. The paper addresses the unpleasant reality that all practitioners know all too well: that is, "… the correlations, as typically measured over the full sample of returns, often belie an asset's diversification properties in market environments when diversification is most needed ...." To resolve this problem, it introduces the concept of "full-scale optimization," an environment in which the component assets exhibit relatively lower correlations on the downside and higher correlations on the upside. Although the math is a bit daunting, the basic concept is well worth consideration for our clients who are "… just like airline pilots—their goal is not to predict the unpredictable, but their portfolios should weather the storm."
"A Discretionary Wealth Approach for Investment Policy," Jarrod Wilcox and Frank Fabozzi, The Journal of Portfolio Management, Fall 2009, pp. 46–59. As with the prior paper, the math is daunting, with references to Bayesian logic, Feller-Lindeberg central limit theorem, and Markov chain Monte Carlo simulations; however, the basic concepts are also potentially very applicable to a practitioner's daily practice. The authors note that subsequent to Markowitz's 1952 contribution, the focus has been on the risk of investment returns with little attention paid to the "often quite large" risk concerning the investor's future source and use of investment funds. This is a risk all too familiar to financial planning practitioners. The discretionary wealth approach is based on the concept of "discretionary wealth," defined as a residual asset in an extended account balance sheet. In this extended environment, the left side of the balance sheet includes the value of current assets and the time-discounted value of foreseen financial contributions. The right side includes current liabilities and the present value of foreseen financial commitments. The difference is "discretionary wealth," and the ratio of the value of the investment portfolio to discretionary wealth is the portfolio's "implied leverage."
"The New Policy Portfolio: Navigating Through Good and
Bad Regimes," Investment Insights, The Investment
Research Journal, Barclays Global, September
2009. This paper is unquestionably my favorite. Using the
same 3P process I apply when selecting managers (philosophy,
process, and people), I found the philosophy underlying the
strategy to be sound, the process reasonably implementable, and the
intellectual capital behind the strategy (Fred Dopfel and Barclays
Global) of the highest caliber. Now the strategy.
Acknowledging that we live in a world of economic uncertainty, the
study addresses the criticism that traditional policy design
assumes "… one central regime and a narrow spectrum of possible
outcomes based on asset class assumptions for that single regime."
To evaluate alternative strategies, and reminiscent of the simple
four-box approach used in the seminal Brinson, Hood, and Beebower
study, this paper considers four economic states or
regimes—a good state coinciding with economic growth,
stability, low inflation, etc.; a bad state coinciding with
economic stagnation or contraction, instability, high inflation,
etc.; and two transition states, that is, good to bad (a crash) and
bad to good (recovery). As Dopfel notes, although this matrix is a
gross simplification, it provides a significant expansion of the
range of outcomes requiring different asset class assumptions for
each state. The result of this simple framework is a non-normal
distribution of returns with higher than expected frequencies of
down markets (that is, fat tails); exactly like the real world.
Dopfel then evaluates the actions and results for four different investors:
Strategic Investors
Naive—Only understands the characteristics of the good state and is unable to anticipate transitions. Investments are optimized based on a good state and remain static. The most common approach today.
Smart But Humble (SBH)—Understands characteristics of all states and transitions but is unaware of the current state or transitions. Investments are static but optimized based on weightings reflecting all states, including transitions.
Tactical Investors
Myopic—Understands characteristics of all states and is aware of the current state, but is unable to anticipate transition. Shifts portfolio to reflect an optimal allocation for the current state.
Prophetic—Understands everything and accurately anticipates all.
The study concludes, not too surprisingly, that anyone skillful
enough to be prophetic should do so, as their results set the upper
boundary for investment performance. Less obvious but intriguing
for mere mortal advisers is the conclusion that the SBH investor
significantly outperforms both the naive and myopic alternatives.
As the executive summary concludes, the SBH success is attributable
to a policy that "… accounts for the additional uncertainty present
in the regime framework (smart) while avoiding the low-breath
tactical bets (humble). By hedging against unfavorable regimes, SBH
also limits his [or her] exposure to downside returns. In response
to critics of the old policy portfolio, the SBH portfolio within a
regime framework is a model for a new policy portfolio that is
'strategic, but hedged.'" As I'm humble enough to know I'm not
prophetic, I will be actively reviewing our policy design process
to see how we might move from naive to SBH.
As always, I hope you found this series of reviews of assistance in
your practice. I look forward to thoughts and suggestions you might
have for future columns.
Endnote
- If you find yourself dozing off skip to the end, as the last one I discuss ("The New Policy Portfolio") is the one I consider most exciting.
