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Filtering Returns for Unspecified Biases in Priors when Testing Asset Pricing Theory

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  • Peter Bossaerts

Abstract

Procedures are presented that allow the empiricist to estimate and test asset pricing models on limited-liability securities without the assumption that the historical payoff distribution provides a consistent estimate of the market's prior beliefs. The procedures effectively filter return data for unspecified historical biases in the market's priors. They do not involve explicit estimation of the market's priors, and hence, economize on parameters. The procedures derive from a new but simple property of Bayesian learning, namely: if the correct likelihood is used, the inverse posterior at the true parameter value forms a martingale process relative to the learner's information filtration augmented with the true parameter value. Application of this central result to tests of asset pricing models requires a deliberate selection bias. Hence, as a by-product, the article establishes that biased samples contain information with which to falsify an asset pricing model or estimate its parameters. These include samples subject to, e.g. survivorship bias or Peso problems. Copyright 2004, Wiley-Blackwell.

Suggested Citation

  • Peter Bossaerts, 2004. "Filtering Returns for Unspecified Biases in Priors when Testing Asset Pricing Theory," Review of Economic Studies, Oxford University Press, vol. 71(1), pages 63-86.
  • Handle: RePEc:oup:restud:v:71:y:2004:i:1:p:63-86
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    File URL: http://hdl.handle.net/10.1111/0034-6527.00276
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    Cited by:

    1. Cogley, Timothy & Sargent, Thomas J., 2008. "The market price of risk and the equity premium: A legacy of the Great Depression?," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 454-476, April.
    2. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    3. Chen, Anlin & Chiou, Sue L. & Wu, Chinshun, 2004. "Efficient learning under price limits: evidence from IPOs in Taiwan," Economics Letters, Elsevier, vol. 85(3), pages 373-378, December.
    4. Potì, Valerio & Levich, Richard M. & Pattitoni, Pierpaolo & Cucurachi, Paolo, 2014. "Predictability, trading rule profitability and learning in currency markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 117-129.

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