Predicting Risk: Some New Generalizations
AbstractExisting 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 38 (1992)
Issue (Month): 1 (January)
systematic risk; Bayesian; shrinkage estimators; forecasting;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If references are entirely missing, you can add them using this form.