Richard Marston certainly has the credentials to author a book on portfolio design. Currently the academic director of the Private Wealth Management Program at the Wharton School of University of Pennsylvania, he has taught in five countries, is the recipient of both a Rhodes Scholarship and a Fulbright Fellowship, and—perhaps most relevantly—has taught asset allocation to more than 5,000 financial advisers as a faculty member in the Certified Investment Management Analyst program. Marston has accomplished what many investment academics find difficult—namely, produce a book that is truly practical and “hands-on” for both financial advisers and investors. Portfolio Design: A Modern Approach to Asset Allocation deftly combines rigorous academic research with everyday investment experience to provide a guidebook to the complexities underlying portfolio design and asset allocation.
The first two chapters alone are worth the price of the book. Marston presents the long-term returns on equities and bonds, giving a much-needed perspective on how extensively returns vary over the short run from the long-run averages. Although his discussion is not necessarily groundbreaking, it does provide a solid foundation for much of the material that follows. Marston also highlights the difference between historical real and nominal returns, which many investors mistakenly ignore when reviewing past returns.
Perhaps the most eye-opening statistics presented in the book are the performance comparisons between nondiversified and diversified portfolios following an economic recession. With the meltdown of 2008 and its concomitant “failure” of diversification so fresh in our minds, Marston’s argument that this particular period was not as exceptional as many commentators have led us to believe is especially enlightening. Switching from an equity portfolio holding the S&P 500 Index to one holding a wider variety of equities increased performance during only three of the periods shown in Table 1. Even so, the benefit was minimal. As Marston points out later in the book, however, a true diversified portfolio (with such alternative assets as managed futures) would have improved performance significantly. This not-so-small detail often seems to be overlooked by those who proclaim that there was no “safe harbor” during the latest market calamity.
|S&P 500 Peak/Trough||70% S&P 500/30% Bondsa||Diversified Stock/Bond Portfoliob|
|Jan 73–Dec 74||–24.9%||–24.2%|
|Nov 80–Jul 82||–6.3||–4.9|
|Jun 90–Oct 90||–9.4||–9.7|
|Aug 00–Feb 03||–26.1||–18.8|
|Oct 07–Mar 09||–33.5||–37.3|
aBonds reflect an investment in the Ibbotson Long Term Treasury bond index prior to 1976 and the Barclays Capital Aggregate Bond Index afterward.
bThe diversified portfolio consists of 30 percent Barclays Capital Aggregate Bond Index, 40 percent Russell 3000 Index, 15 percent MSCI EAFE Index, 10 percent FTSE NAREIT U.S. Real Estate Index, and 5 percent MSCI Emerging Markets Index.
Sources: Barclays Capital; Russell Investments; Morgan Stanley Capital International; FTSE; Morningstar.
This conclusion and others like it demolish many common investment misconceptions that plague even the most seasoned investors. The impact of these lessons is amplified by Marston’s ability to present his research results in easy-to-read tables and graphs that require little additional explanation. Many investment authors could learn from his clear and economical approach to data analysis.
The second part of the book consists of chapters devoted to specific investment classes. Marston provides long-term performance analysis of small-cap stocks, value versus growth stocks, foreign stocks, emerging market stocks, and both domestic and foreign bonds. The chapters are all organized in a similar manner, beginning with the stand-alone performance of the asset, followed by a display of how a portfolio would fare when that asset is added to a generic holding of stocks (S&P 500) and bonds (long-term U.S. Treasuries). Each analysis details the risk associated with the indicated return by showing both the standard deviation and the Sharpe ratio. Many chapters also include alpha as a risk-adjusted measure.
Marston debunks numerous pieces of conventional wisdom. The shibboleths and the asset classes with which they are associated include the January effect and the Santa Claus rally (small-cap stocks), the value-added effects of currency hedging and geographical diversification (foreign stocks and bonds), and the equating of GDP growth with stock market returns (emerging stocks).
Along with his myth busting, Marston confirms the benefits of exploiting certain market inefficiencies. One example is the mystifying performance advantage of mid-cap stocks over large- and small-cap stocks. His discussion would have benefited from a more thorough examination of the possible explanations for the anomaly. The mid-cap effect has been generally attributed to data mining or regarded as simply an artifact of market history. Marston also shows that value stocks have outpaced their growth counterparts over virtually every period studied.
Marston goes on to demonstrate that foreign stocks, both developed and emerging, have largely lost their investment luster owing to an ever-increasing correlation with domestic stocks. He delves into considerable detail as he breaks out the effects of American Depositary Receipts (ADRs), multinationals, and global exchange-traded funds. This drill-down is highly beneficial for the many investors who mistakenly believe they can achieve diversification simply by owning an ADR or two.
After the discussion of traditional assets, Marston analyzes alternative investment classes, including hedge funds, venture capital, private equity, real estate, and commodities. A chapter on strategic asset allocation begins the third section of the book. Marston again does a fine job, taking a complex subject and distilling it into its essential components. He introduces the concepts of the efficient frontier and portfolio optimization.
Unlike the many authors who cover portfolio theory by reproducing the obligatory “fishhook” graph depicting the trade-off between risk and return, Marston adds color by succinctly explaining the mathematics behind the graph. He does so in a decidedly accessible manner without glossing over the salient concepts. Perhaps the best example of this approach is his discussion of the “dirty secret of optimization.” Marston exposes perhaps the most significant shortcoming of traditional Markowitz-based optimization, which is the idea of portfolio constraints. When asset data are fed into an optimizer, the “optimal” portfolio that emerges often consists of highly nondiversified allocations that are impractical to implement with actual client portfolios. In contrast to several previous sections in which Marston merely skims the surface, here he wisely goes into more depth by discussing a leading alternative approach to optimization, the Black–Litterman method.1 Although this subject could easily warrant a book of its own, Marston condenses the relevant material into a few highly readable and informative pages.As with his treatment of traditional asset classes, Marston presents many tables and graphs that summarize the effectiveness (or lack thereof) of adding alternative assets to a traditional portfolio. His findings are mixed. In the case of hedge funds, after accounting for the various biases of hedge fund returns (backfilling, self-selection, etc.), he shows that a traditional portfolio is only minimally affected by their inclusion. Many of the same data-related drawbacks and difficulties adversely affect venture capital and private equity. Homeowners will surely be dismayed by the reported “home ownership returns,” which take into account the erosive effects of inflation and the costs of upkeep, not to mention the absolute downdraft in prices following the recent unpleasantness in real estate investing.
Moving on to commodities, Marston once again slays some long-held beliefs, such as the notion that commodities provide noncorrelated, high absolute returns while serving as an effective hedge against inflation. Although some of these results have been observed historically, it is certainly not a foregone conclusion that they will persist in the long term. For example, from February 1991 to June 2009, commodities, as measured by the Goldman Sachs Commodity Index, had a correlation of 0.34 with the U.S. Consumer Price Index. Marston also points out the peril in relying on long-only investments in commodities, reminding us of the drubbing they took in 2008, together with virtually every other asset class.
Wrapping up the discussion on alternative investments, Marston turns his attention to the performance of the Yale Endowment. Although much has been written about Yale investment chief David Swensen’s impressive record over the past decade, the fund’s more recent performance has not received the same level of scrutiny. Did investing heavily in alternatives benefit the Yale Endowment? The answer is yes and no. For the fiscal year ended June 2009, the fund experienced a loss of 24.6 percent, which beat most traditional equity asset classes but still represented a substantial drawdown for the endowment.2 Marston explores several reasons for the Yale Endowment’s performance relative to other endowments and explains how the everyday investor can benefit, at least in part, from Swensen’s experiences.
The final chapters touch on investing and spending by foundations and retirees. Marston discusses the basics of spending rules, including Monte Carlo simulations and real versus nominal returns, straightforwardly, without excessive detail or mathematical complexity. In conjunction with this discussion, he lays out the benefits of rebalancing funds.
Portfolio Design is a timely, well-written text on the fundamentals of asset class investing and asset allocation techniques. Although the book would have benefited from more detail and analysis in some sections, Marston does a commendable job of distilling complex topics into a concise, accessible work that should find a place on the bookshelf of every investor who seeks to benefit from intelligent asset allocation.