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Predicting Risk: Some New Generalizations

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  • G. Andrew Karolyi

    (Academic Faculty of Finance, Ohio State University, Columbus, Ohio 43210)

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    Abstract

    Existing adjustment techniques for forecasting systematic risk of individual firms have been based on relatively uniformative prior knowledge about the cross-sectional distribution of risk estimates. This study introduces prior information in the form of size and industry-based cross-sectional distributions of risk estimates. Such information is incorporated into forecasts using familiar and generalized adjustment techniques, the latter being based on recently developed multiple shrinkage methods. Improved forecast performance results.

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    File URL: http://dx.doi.org/10.1287/mnsc.38.1.57
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 38 (1992)
    Issue (Month): 1 (January)
    Pages: 57-74

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    Handle: RePEc:inm:ormnsc:v:38:y:1992:i:1:p:57-74

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    Related research

    Keywords: systematic risk; Bayesian; shrinkage estimators; forecasting;

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    Cited by:
    1. Lee, Kuan-Hui, 2005. "The World Price of Liquidity Risk," Working Paper Series 2006-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    2. Tusell Palmer, Fernando Jorge & Esteban González, María Victoria, 2009. "Predicting Betas: Two new methods," BILTOKI, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) 2009-01, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    3. Muradoglu, Gulnur & Zaman, Asad & Orhan, Mehmet, 2003. "Measuring the Systematic Risk of IPO’s Using Empirical Bayes Estimates in the Thinly Traded Istanbul Stock Exchange," MPRA Paper 13879, University Library of Munich, Germany.

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