Volume 6, No. 3, Third Quarter 2008

Where Do Alphas Come From?: A New Measure of the Value of Active Investment Management

by: Andrew W. Lo

The value of active investment management is traditionally measured by alpha, beta, volatility, tracking error, and the Sharpe and information ratios. These are essentially static characteristics of the marginal distributions of returns at a single point in time, and do not incorporate dynamic aspects of a manager’s investment process. In this paper, I propose a measure of the value of active investment management that captures both static and dynamic contributions of a portfolio manager’s decisions. The measure is based on a decomposition of a portfolio’s expected return into two distinct components: a static weighted-average of the individual securities’ expected returns, and the sum of covariances between returns and portfolio weights. The former component measures the portion of the manager’s expected return due to static investments in the underlying securities, while the latter component captures the forecast power implicit in the manager’s dynamic investment choices. This measure can be computed for long-only investments, long/short portfolios, and asset allocation rules, and is particularly relevant for hedge-fund strategies where both components are significant contributors to their expected returns, but only one should garner the high fees that hedge funds typically charge. Several analytical and empirical examples are provided to illustrate the practical relevance of this decomposition.

Optimal Trading Strategy with Optimal Horizon

by: Edward E. Qian

Portfolio implementation is an essential part of active investment strategies. The trading horizon-the length of time allocated for trade implementation, is an important consideration in portfolio trading. Previous research on optimal trading limits the trading horizon as a fixed value. In this paper, we treat it as an endogenous factor and find the optimal trading horizon as a part of optimal trading strategy to further reduce trading costs. We derive analytical results for optimal trading strategy with optimal horizon and provide numerical examples for illustration.

The Structure of Hybrid Factor Models

by: Jose Menchero and Indrajit Mitra

We study the problem of augmenting fundamental risk models with statistical factors in order to capture the risk associated with omitted factors. The statistical factors are estimated by applying principal component analysis to the cross-sectional residuals. We show that in the limit of zero noise, the statistical factors can be precisely interpreted as fundamental factors that have been Gram-Schmidt orthogonalized to the existing fundamental factors. For finite noise, we determine the correlations between the true and estimated factor exposures and returns. This establishes a practical criterion for the successful detection of hidden factors.

A Structural Analysis of the Default Swap Market, Part 1 (Calibration)

by: Lisa R. Goldberg, Rajnish Kamat and Vijay Poduri

We analyze the default swap market with the two factor I2 structural model, which is driven by firm value and firm leverage. As we show empirically, the de- fault swap market incorporates these risks differentially over time, by region, by industry, and by coarse quality. This leads us to pool firms with similar character- istics into calibration groups whose parameters are used to align model and market sensitivities to the risk factors. We include equity factor returns to account for contagion and momentum effects for industries or credits that have suffered recent downturns. The close alignment of our model spreads with the market enables us to extract systematic effects reflected in the dynamics of average levels of model inputs and outputs, and discern relative value among credits by analyzing model errors. Applications of our model include assessment of relative value, pricing of illiquid names, cross market hedging and monitoring credit portfolios. A rich-cheap portfolio construction strategy based on our model shows consistent profits in most calibration groups between January 2004 and May 2006.

Humpbacks in Credit Spreads

by: Deepak Agrawal and Jeffrey R. Bohn

Models of credit valuation generally predict a hump-shaped spread term structure for low quality issuers. This is understood to be driven by the shape of the underlying conditional default probabilities curve. We show that (a) recovery assumptions and (b) deviation of bond's price from its par value can also drive different term structure shapes. Our analysis resolves conflicting empirical evidence on the shape of speculative grade spread curves and explains the related existing theoretical results. On examining a large set of speculative grade bonds and credit default swaps, we find evidence that par-spread term structures are likely to be downward sloping as credit quality deteriorates sufficiently.

Case Studies

by: Jack L. Treynor

“Case Studies” presents a case pertinent to contemporary issues and events in investment management. Insightful and provocative questions are posed at the end of each case to challenge the reader. Each case is an invitation to the critical thinking and pragmatic problem solving that are so fundamental to the practice of investment management.

The Age of Turbulence: Adventures in a New World

by: Alan Greenspan • reviewed by: Bruce Grantier

“Book Reviews” identifies important, and often popular, new books from a wide range of investment topics. Beyond providing a summary and review of the content and style of the books, “Book Reviews” seeks to contribute to a conscious, critical, and informed approach to investment literature.

Practitioner’s Digest • Vol. 6, No. 3

The “Practitioners Digest” emphasizes the practical significance of manuscripts featured in the “Insights” and “Articles” sections of the journal. Readers who are interested in extracting the practical value of an article, or who are simply looking for a summary, may look to this section.