By Samuel Lum, CFA
If the global financial crisis has left us with any enduring lessons, it’s that asset return distributions can be significantly skewed and asymmetrical, and that fat tails are the norm rather than the exception. So how can investment practitioners manage this reality? That question animated a recent presentation by Peng Chen, CEO Asia (ex-Japan) of Dimensional Fund Advisors, at the CFA Institute Thailand Investment Conference, which was cosponsored with CFA Society Thailand and the Securities Exchange Commission Thailand. (You can watch a replay of Chen's 56-minute presentation on our blog.)
As Chen observed, the global crisis that began in 2008 has called into question many of the basic assumptions and central tenets of modern portfolio theory (MPT). But, in fact, the world of investing has long been observed to be "non-normal" insofar as asset returns historically have not followed a normal, or Gaussian distribution, and correlations, rather than being stable, have varied significantly across different market regimes. The result is that the benefits of portfolio diversification, the discipline of adhering to a strategic asset allocation policy, and other practical implications of MPT are being challenged.
After providing a brief overview of traditional MPT as it was first developed by Harry Markowitz in 1952 and enhanced in the following decades by numerous scholars and financial economists -- including William Sharpe, Robert Merton, and Eugene Fama -- Chen addressed two key questions:
- Did asset allocation and portfolio diversification fail?
- How should asset allocation and portfolio diversification be implemented in a non-normal world?
On this first question, Chen contended that diversification in fact did not fail at the security level and the basic asset class (stocks, bonds, and cash) level. However, the increasing globalization of economic activity and capital markets has made stock markets around the world much more highly correlated, reducing the benefits of diversification across these markets, especially during periods of crisis.
In addition, diversification into alternative assets such as commodities, real estate, private equity, and hedge funds did not appear to provide much benefit. In a recent empirical study, Peng and his former colleagues at Ibbotson Associates found that many hedge fund strategies have significant systematic, or beta, risk embedded in them, so the diversification benefit of combining hedge funds with traditional asset classes like stocks and bonds is limited. Moreover, the average alpha of hedge funds is more than offset by high fees, which typically include a significant incentive component, and the alpha is in fact declining over time as the hedge fund industry grows and opportunities to exploit inefficiencies remain more or less the same.
Active managers, on average, do not add value because chasing alpha is a zero sum game, Chen argued, or even a negative sum game after trading costs and the high fees are accounted for. It is also very difficult to identify truly skillful managers who consistently outperform over long periods.
With regard to the second question above, Chen introduced as an improvement to the normal distribution the truncated Lévy flight (TLF) distribution, which accounts for "higher moments" (in a statistical sense) of skewness and kurtosis, in addition to the first moment (mean) and the second moment (variance). Asset returns, Chen argued, are better depicted by the TLF distribution, which provides a more effective tool to analyze downside risk. Instead of mean-variance optimization under MPT, an approach using mean-conditional value-at-risk optimization could be adopted to come up with an optimal asset allocation, he added.
Chen concluded with his asset class performance outlook. As he examined return on bonds vs. stocks over the last 40 years, he found that most of the total return from bonds came from the coupon income. With bond yields at historic lows, he said he finds it hard to see bonds outperforming stocks over the next several years.
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