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The Likelihood of Various Stock Market Return Distributions, Part 2: Empirical Results

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  • Markowitz, Harry M
  • Usmen, Nilufer

Abstract

The present article shows how Bayesians should shift beliefs among a family of models concerning the probability distribution of daily changes in the Standard & Poor 500 Index, given a particular sample. The preceding article in this issue showed that classical (R. A. Fisher, Neyman-Pearson) inference can be highly misleading for Bayesians, as can the assumption of a diffuse prior. The present article discusses how to bound Bayesian shifts in belief for compound hypotheses generally, as well as the specific shifts in beliefs among simple and compound hypotheses implied by the particular sample. Copyright 1996 by Kluwer Academic Publishers

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Bibliographic Info

Article provided by Springer in its journal Journal of Risk and Uncertainty.

Volume (Year): 13 (1996)
Issue (Month): 3 (November)
Pages: 221-47

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Handle: RePEc:kap:jrisku:v:13:y:1996:i:3:p:221-47

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Web page: http://www.springerlink.com/link.asp?id=100299

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Cited by:
  1. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
  2. Kevin Fergusson & Eckhard Platen, 2006. "On the Distributional Characterization of Daily Log-Returns of a World Stock Index," Applied Mathematical Finance, Taylor & Francis Journals, vol. 13(1), pages 19-38.

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