Hossein B. Kazemi

Understanding Hedge Fund Performance: Research Issues Revisited—Part II

In this article, the authors briefly review the potential market factors affecting various hedge fund strategies. The market factors affecting hedge fund returns are based on the underlying securities held and the trading philosophy behind each strategy. A simplified multi-factor model is used to capture the market factors driving various hedge fund strategies, and the actual performances of various hedge fund strategies relative to these market based factors are presented. The market factors are also used to illustrate the relative performance of various hedge fund strategies conditional on extreme values of these market factors. The empirical relationship between the measured market factors and various hedge fund strategies over time is also explored. Results show that while for style pure indices of hedge fund performance the factor relationships remain fairly constant, for diversified funds of funds, which may dramatically change their strategy, the factor loadings that explain fund of fund returns change. These results imply that for funds of funds, which emphasize market timing, their benefit in terms of systematic asset allocation is also time varying.

Understanding Hedge Fund Performance

This article is the first of a two-part review of various micro (fund) and macro (strategy) factors that impact fund performance. In this part, the authors concentrate on reviewing some of the micro (e.g., fund level) elements driving fund performance. Specifically, they analyze the impact of fund characteristics such as survivor bias, age, and size on the funds performance. In some cases, the results presented in this article seem to question previous results such as the impact of stale prices on return relationships, survivor bias, the use of historical hedge fund index data, and incentive fees. In other cases, the results support previous research on issues such as performance persistence, lock-ups, and a number of other micro/fund effects.

The Impact of Leverage on Hedge Fund Risk and Return

As in the case of traditional investments, hedge funds are often compared on a risk adjusted basis. Risk adjustment is of particular importance for hedge fund analysis since two funds may differ solely by leverage, such that they may differ on an absolute return basis, but be similar on a risk adjusted basis. While leverage should theoretically not affect the level of risk adjusted return within a strategy, it is possible that funds which use higher levels of leverage may in fact trade differently than funds using lower levels of leverage. In this article, the effect of leverage on hedge fund risk and return is analyzed. In brief, results are presented on the level of leverage used in various hedge fund strategies. Results are also provided on the degree to which leverage above or below the median fund leverage results in superior or inferior risk adjusted performance within a particular hedge fund strategy. Overall the results show that while different hedge fund strategies may use different amounts of leverage, within a particular hedge fund strategy, there is little evidence of a significant difference between risk adjusted performance of funds with above-median and below-median leverage.

Momentum in Asset Returns: Are Commodity Returns a Special Case?

This article reviews research on momentum in asset markets, with an emphasis on research involving momentum in commodity markets. Commodity markets are different than the markets for financial assets, such as stocks and bonds. Storage costs, inventory levels, and hedging demand by suppliers and producers influence commodity prices in ways that may not be observed in other asset classes. Research indicates that momentum profits are related to these market structure factors. The persistence of momentum in commodity markets has implications for investment products that incorporate commodities. The popularity of commodity investments among institutional investors has increased dramatically in the past decade. While some investors have allocated funds to hedge funds that incorporate momentum-based strategies, most of these investments are in indices that do not have a momentum component to the return. Research indicates that adding a momentum component to a commodity portfolio may provide strategic benefits in the form of higher risk-adjusted returns and reduced volatility.

Hedge Fund Database 'Deconstruction': Are Hedge Fund Databases Half Full or Half Empty?

While the impact of backfill bias, survivor bias other database construction issues (e.g., onshore versus offshore) on hedge fund performance have received considerable research attention, the impact on hedge fund performance of differences in the underlying quality or number of reporting managers in various hedge fund databases has often been under reported. Most major hedge fund databases are based on ‘manager’ based reporting. As a result database quality is dependent on managers updating requested data. In addition, hedge fund databases were created and grew at different times. Thus large differences in the number of managers reporting as well as differences in other fund platform characteristics may exist between various databases. If these databases contained enough manager breadth and depth, results at the portfolio level could be similar across various databases, however, differences may still exist at the average manager level especially for small subsets of analysis (e.g., strategy, fee level, etc.). In this analysis we compare performance characteristics of two major databases often used in hedge fund analysis (CSFB/Tremont and CISDM). More specifically, we compare performance results at the strategy level for 1) all reporting funds, 2) funds denominated only in U.S. dollars and 3) a cleaned set of funds with duplicates removed (e.g. multiple share classes or currencies). Results show some return and risk differences between the two databases at the portfolio and average manager level. These differences, however, are often relatively small. In the end, the impact of database usage and the necessity to ‘deconstruct’ one’s database depends, in part, on whether one views the glass as half full or half empty.

Collaring the Cube: Protection Options for a QQQ ETF Portfolio

This article assesses the effectiveness of a long collar as a protective strategy. It examines the risk/return characteristics of a passive collar strategy on the Powershares QQQ trust exchange-traded fund from March 1999–2008 and finds that, over this time period, a six-month put/one-month call collar provides far superior returns to the buy-and-hold QQQ strategy with significantly less volatility. Since returns from protective strategies are not normally distributed, both Leland alpha and the Stutzer index are used to measure risk-adjusted performance. In addition, a number of implementations of a long collar strategy are considered, where for each strategy the impact of bid/ask spreads on the strategy9s perfor mance is taken into account. To examine the collar9s performance in different market environments, the time period is further segmented into two sub-periods, an early period that is generally favorable to the collar and a later period that is unfavorable to a collar strategy. The magnitude of the risk reduction of the collar is significant.

Replication and Benchmarking of Hedge Funds

The growth in the hedge fund industry during the last two decades has been accompanied by a general decline in the performance of hedge funds. Academic research on hedge funds has led to the development of a number of replication strategies that in some cases can explain a significant portion of returns generated by various hedge fund strategies. This article presents a replication methodology that is particularly suited for performance evaluation. The methodology develops two replicating portfolios such that the distribution properties of the target are matched. The first portfolio delivers the statistical properties at the lowest possible cost while the other is more expensive but delivers the same set of properties as the target. The portfolios are used to evaluate a set of managers reporting to the CISDM Database.

Hedge Fund Return-Based Style Estimation: A Review on Comparison Hedge Fund Indices

The data dependency of empirical financial research is of common concern to both academics and practitioners. This is especially true for hedge funds since no one single commonly accepted database exists and since many of the databases may hold different sets of reporting managers. Each database uses current reporting managers as the basis for the construction of hedge fund indices and these index returns reflect the characteristics of the funds reporting to the relevant database. However, unlike historical returns derived from current databases, historical returns from most major hedge fund indices do not contain backfill or survivor bias. At the same time, performance characteristics may differ between indices since each index is constructed based on a different set of rules (e.g., equal weighted, asset weighted, etc.). In this analysis we conduct a series of empirical tests, similar to those previously conducted in academic studies. In this analysis we use only those hedge fund indices which reflect the average returns of the entire set of reporting managers; that is, the indices representing overall industry returns. Results indicate that return based style analyses, often used as a basis for hedge fund analysis, are impacted both by the period of analysis as well as the hedge fund index used. Moreover, results indicate that the addition of variables beyond those designed to capture underlying equity, interest rate, and credit risk have little impact on explanatory power of these hedge fund universe indices beyond a very low level of statistical significance.

Demand and supply of forward exchange contracts under incomplete information

Abstract This article derives a complete set of demand and supply functions for forward exchange contracts in a multiperiod economy under incomplete information. Investors can invest in domestic and foreign risky securities; they consume foreign as well as domestic goods that have stochastic prices. Because the aggregate exposure to exchange risk may be different from zero and because investors may have heterogeneous expectations, they take speculative positions. The central theme of the article is an analysis of the role of forward exchange contracts and the effects of incomplete information in the optimal allocation of exchange risk.

Asset Class and Strategy Investment Tracking Based Approaches

In recent years, there has been a dramatic increase in the number of systematic algorithmic products that attempt to capture the risk and return of a particular asset class or fund strategy. These products may be stand-alone investments created to provide direct “replication” (e.g., almost identical securities) of a comparison benchmark or they may be constructed expressly to “track” (e.g., similar but not identical securities) an existing non-investable or investable benchmark. Various approaches exist in the creation of these tracker products. In this article, the authors review alternative approaches to the creation of investment trackers. The authors concentrate on the underlying rationale for fund tracker products, the alternative approaches often employed to create such products, and practical concerns related to strategy or fund tracking based products. They also provide a brief review of the performance of existing tracker products as well as examples of tracker products use in multi-asset allocation.