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Tracking Asset Volatility By Means of a Bayesian Switching Regression

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  • Mehta, Cyrus R.
  • Beranek, William

Abstract

It is often desirable to know whether or not a risky asset's beta coefficient has changed and, if so, at what point in time the change occurred. For example, this knowledge is of obvious importance to beta-using security analysts and portfolio managers. As another example, a given theory may imply that a particular firm's beta should have changed at different points in time. Investigators may want to test such a hypothesis. Furthermore, tests are frequently performed on the effects of events on residuals of the market model, tests requiring the assumption of beta stability. For these, and possibly other reasons, it is useful to be able to detect that a change in beta did, in fact, take place as well as, in some instances, identifying the point in time at which the change took place.

Suggested Citation

  • Mehta, Cyrus R. & Beranek, William, 1982. "Tracking Asset Volatility By Means of a Bayesian Switching Regression," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(2), pages 241-263, June.
    • Handle: RePEc:cup:jfinqa:v:17:y:1982:i:02:p:241-263_01
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    Cited by:

    1. Edward Lawrence & Gordon Karels & Arun Prakash & Siddharth Shankar, 2011. "Effect of regulation FD on disclosures of information by firms," Applied Financial Economics, Taylor & Francis Journals, vol. 21(13), pages 979-996.
    2. Ellul, Andrew, 2006. "Ripples through markets: Inter-market impacts generated by large trades," Journal of Financial Economics, Elsevier, vol. 82(1), pages 173-196, October.
    3. Burnett, John E. & Carroll, Carolyn & Thistle, Paul, 1995. "Implications of multiple structural changes in event studies," The Quarterly Review of Economics and Finance, Elsevier, vol. 35(4), pages 467-480.

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