The asset class managed futures has not been well documented, even though it has been around for more than 30 years and exceeds $220 billion in assets under management. Consequently, any book on the subject immediately piques my interest. The latest offering is Managed Futures for Institutional Investors: Analysis and Portfolio Construction, by Galen Burghardt and Brian Walls, both executives at Newedge USA with decades of managed futures experience from every standpoint, including investment research, brokerage services, trading, operations, and capital introduction services. This exceptional breadth of direct knowledge enables the authors to cover a wide swath of information in great detail and with numerous real-life examples to support their assertions.
Managed Futures is really two books in one. On the one hand, it is a textbook on the nuts and bolts of managed futures that any business school would be wise to incorporate into its curriculum (assuming that any schools are even offering instruction in this overlooked asset class). Written in a highly approachable and user-friendly manner,Managed Futures is replete with tables, charts, and graphics that enhance the exposition, resulting in a very fluid read that follows a natural path through the material.
On the other hand, Managed Futures is a conventional “How to Make Money in [fill in the blank]” book. Burghardt and Walls step back from the inner workings of the asset class and introduce several trading methods for successfully incorporating managed futures into a portfolio. Most of these methods can also be used to trade other asset classes, including equities, exchange-traded funds (ETFs), and options. This fungibility lends credence to the recommended approaches because it demonstrates that they have not been overoptimized to fit the authors’ handpicked examples. The systems presented are both simple (without being simplistic) and intuitive. Although the authors’ presentation may not appear to be groundbreaking, to be offered straightforward trading methods without an excessive number of variables, potential curve fitting, or data mining is refreshing.
In a clever touch, Burghardt and Walls deftly combine the book’s two aspects into a section titled “Portfolio Construction,” which presents detailed original research in a woefully neglected area of portfolio design—namely, when and how to replace assets (or asset managers, as the case may be) effectively and efficiently. Briefly, the research revolves around the much-discussed concepts of persistency and predictability in asset returns, risk, and correlation. As many prior studies have shown, returns are the most difficult factor to predict—and correlations the easiest—on the basis of past data points. Risk falls somewhere in between. Again, these ideas may not be new to the reader, but the authors put them into practice by exploiting the relative predictability of correlations in order to design portfolios with attractive risk–return profiles.
For practitioners who are considering offering managed futures to their clients through commodity trading advisers (CTAs), Burghardt and Walls present intriguing original research on constructing an optimal portfolio of multiple managers. They begin by addressing the question of diversification: How many CTA programs are needed to achieve a specified level of diversification? This question has been studied numerous times in connection with hedge funds, mutual funds, and individual stocks, and so the results do not come as a complete surprise. Because CTAs are generally a homogeneous group, however, the optimal number of holdings of CTAs tends to be less than for hedge funds. The authors find that most of the potential gains from diversification can be obtained by holding just five or six CTAs. When constructing a portfolio of CTAs, this information is vital because it can greatly reduce the time and expenses involved in conducting due diligence and handling other compliance-related issues.
In arriving at their conclusions, the authors rely heavily on index-based data. Accordingly, Managed Futures devotes substantial space to various biases that can occur in index data (selection, backfill, etc.), as well as the absolute quantity of data available to the researcher. Especially illuminating is the section on daily data versus monthly data. When designing a system by using ETFs or common stock, the natural choice is daily or even intraday data. In the managed futures arena, however, most returns are posted monthly, with daily data the rare exception. Moreover, the indices consist of CTAs, not individual assets, which makes data collection comparatively difficult.
Burghardt and Walls go on to demonstrate the potentially deleterious effects of lacking sufficient data points while relying on such standard measures as variance and correlation. One drawback to daily data is the “noise” that may be present, which can obscure the overall “signal” of the data. They note that monthly data may alleviate the problem, but at the cost of having too few data points. In addition, monthly periodicity results in lagged signals. Although converting the daily data into weekly data might represent an effective compromise, the authors do not explore that possibility. Perhaps future research will address this issue.
Investment professionals, institutional or otherwise, who contemplate adding managed futures to their arsenal are strongly advised to seek out this book.Managed Futures provides both the solid theoretical underpinnings of the asset class and the practical aspects of incorporating managed futures into a client’s portfolio.