Schneeweis, Crowder, and Kazemi, The New Science of Asset Allocation

Asset allocation is a topic that has long fascinated me; I’m infatuated with the idea of moving parts that sometimes correlate and sometimes don’t, that sometimes spike and sometimes dive all being blended into portfolio that can outperform benchmarks, sometimes significantly. Individual investors are usually told to diversify among stocks, bonds, and perhaps real estate and commodities and periodically rebalance. The recommended percentage to allocate to each asset class may vary somewhat from person to person depending on age and risk tolerance, but the general principle is simple and straightforward. Unlike many other recommendations from financial advisors, it’s not even obviously wrong. It’s just boring and intellectually unsatisfying.

Thomas Schneeweis, Garry B. Crowder, and Hossein Kazemi teamed up to write The New Science of Asset Allocation: Risk Management in a Multi-Asset World (Wiley, 2010). As is increasingly the case with financial book titles, this particular title both overpromises and misleads. The book does not blaze new trails, and although it has ample charts, graphs, and the occasional mathematical formula it will not appeal to hard-core quants. That said, the book provides a very readable overview of the tradeoff between risk and return and the role that asset allocation plays in the inevitable balancing act. It provides some intellectual underpinnings to the process of asset allocation, a process that requires both number-crunching and personal judgment. It is also a valuable source of data--for instance, tables that give benchmark returns along with their standard deviations, information ratios, maximum drawdowns, and correlations to other indices.

The book covers a range of topics--risk measurement; alpha and beta; strategic, tactical, and dynamic asset allocation; and core and satellite investment. It also devotes ample space to alternative investments (hedge funds, managed futures, private equity, real estate, and commodities).

Even though I thoroughly enjoyed reviewing material with which I was familiar and occasionally incorporating new insights, I decided for the purposes of this post to look at a simple way to monitor the risk-return profile of a fund or portfolio—adjusting its volatility. The authors argue throughout the book that risk is multidimensional, so this is nothing more than a “quick and dirty” technique. Assume that the five-year historical volatility on a portfolio’s pro-forma returns has been 10% while during the same period the average implied volatility of the U.S. equity market as measured by the VIX has been 18%. That is, the portfolio’s volatility has been about 55% of the VIX. Assume further that the portfolio manager’s job is to keep this ratio roughly constant, increasing portfolio risk if the VIX falls and hedging out some of the portfolio’s volatility with index futures if the VIX spikes. The authors provide the formula for accomplishing this task, a formula that I’ll file away for the time that I am no longer an active trader but have a multimillion dollar portfolio that needs this kind of adjustment, perhaps in my next life.

Okay, so perhaps my readers aren’t all managing funds (though I know that some are) or sitting on multimillion dollar personal portfolios. This book is valuable even for the intraday S&P futures trader, which is why I brought up the portfolio volatility adjustment example. If the VIX gets to elevated levels, portfolio managers who are managing risk start hedging. It’s important to know the depth of the teams on each side of the trade.