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Predicting Risk: Some New Generalizations


  • G. Andrew Karolyi

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


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.

Suggested Citation

  • G. Andrew Karolyi, 1992. "Predicting Risk: Some New Generalizations," Management Science, INFORMS, vol. 38(1), pages 57-74, January.
  • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:1:p:57-74

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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. Villalba-Padilla, Fátima Irina & Flores-Ortega, Miguel, 2012. "Capacidad de predicción de los modelos GARCH simétricos aplicados a variables financieras de México 2001-2011," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(34), pages 81-124, segundo t.
    3. Cederburg, Scott & O’Doherty, Michael S., 2015. "Asset-pricing anomalies at the firm level," Journal of Econometrics, Elsevier, vol. 186(1), pages 113-128.
    4. Martin R. Young & Peter J. Lenk, 1998. "Hierarchical Bayes Methods for Multifactor Model Estimation and Portfolio Selection," Management Science, INFORMS, vol. 44(11-Part-2), pages 111-124, November.
    5. I-Hsuan Ethan Chiang, 2016. "Skewness And Coskewness In Bond Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 39(2), pages 145-178, June.
    6. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Esteban González, María Victoria & Tusell Palmer, Fernando Jorge, 2009. "Predicting Betas: Two new methods," BILTOKI 2009-01, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    8. 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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