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Contributions by Michael Levinson


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  1. PAPER

    Barra Hedge Fund Model (HFM2) Research Notes 

    Jul 2, 2011 Jay Yao , Michael Levinson

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  2. PAPER

    Hedge Fund Risk Modeling 

    Apr 1, 2007 Miguel Alvarez , Michael Levinson

    Factor and Risk Modeling

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    This paper introduces the Barra Hedge Fund Model, designed to overcome the unique challenges of modeling hedge fund risk.  The model provides a forecast of the risk of a hedge fund, or a portfolio of funds, using fund return series and information regarding its peer group membership.  Extensive research has identified factors that drive the returns to securities within each of these peer groups for various asset classes and regions.  What may be surprising to some investors is that many hedge fund managers do not fully hedge their exposure to these factors.  The model uses factors that identify two major sources of hedge fund systematic risk.  A portion of hedge fund risk is due to exposures to familiar factors that underlie conventional investments.   The hedge fund strategy factors capture systematic risk characteristics not fully explained by these traditional factors.   Each fund's exposure to these risks is calculated using a returns-based analysis.  We introduce the Barra hedge Fund Exposure Generator, an adaptive framework for estimating dynamic strategy exposures based upon moving and expanding window regressions, as well as a Kalman filter.  In addition, we address how to select the best factors for modeling a single hedge fund using in-sample and out-of-sample statistical analyses.  Most importantly, this approach can be used to aggregate factor exposures, factor covariance and idiosyncratic risk into a single portfolio risk forecast.  Lastly, we illustrate typical hedge fund style peer group systematic behavior and explain the drawbacks of using hedge fund style indices to model risk.

  3. PAPER

    Returns to E/P Strategies, Higgledy-Piggledy Growth, Analysts' Forecast Errors, and Omitted Risk Factors 

    Nov 1, 1993 Russell Fuller , Michael Levinson , Lex Huberts

    Asset Pricing and Valuation

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    The authors document that high E/P stocks historically have generated positive alphas, and low E/P stocks                                         have generated negative alphas. They attempt to explain this phenomenon by analyzing three variables: earnings growth rates subsequent to forming E/P portfolios, analysts' forecast errors, and possible omitted risk factors. They find these variables do not account for the abnormal returns associated with high and low E/P strategies. Thus, the "E/P effect" remains an enigma.

  4. PAPER

    It's Not Higgledy-Piggledy Growth! 

    Nov 1, 1992 Lex Huberts , Russell Fuller , Michael Levinson

    Asset Pricing and Valuation

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    Contrary to the findings of other studies, the authors of this study find that earnings changes are not randomly distributed. Using earnings-to-price ratio as the market's implicit forecast of future earnings growth, they find that the market appears to differentiate the earnings prospects of companies quite well. On average, high E/P stocks tend to have significantly poorer earnings growth; low E/P stocks tend to have significantly higher earnings growth.

  5. PAPER

    The Institutional Index as an Effective Hedging Tool 

    Jan 1, 1992 Michael Levinson

    Factor and Risk Modeling

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    The American Stock Exchange in late 1986 unveiled a 75-stock capitalization weighted index. This institutional index, known as the "XII," consists of publicly traded companies held by institutional portfolios in the greatest dollar amount. The XII, as the epitome of institutional portfolios' holdings, can be expected to track both their characteristics and their performance much more closely than most, if not all, broader-based alternatives. At the very least, trading 75 XII stocks is certainly less costly than maintaining a basket comprised of all S&P 500 companies. In this article, we will examine the XII Index as both a proxy for and an alternative to the S&P 500  Index. We will first identify the major differences between the XII and the S&P 500. This analysis incorporates the results obtained using Barra's PERFormance ANalysis (PERFAN) software. We will then compare their effectiveness as a hedge in three separate case studies. These studies rely on Barra's U.S. Interactive Portfolio Risk Characterization (IPORCH) software to facilitate each hedge's construction. These hedges will be formed from the XII and the S&P 500 both individually and in combination with other indexes. Our studies use managed portfolios of various growth characteristics to examine the effectiveness of the XII relative to the S&P 500 under a variety of circumstances.