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Are Stock Returns Predictable? A Test Using Markov Chains

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Author Info
McQueen, Grant
Thorley, Steven
Abstract

This paper uses a Markov chain model to test the random walk hypothesis of stock prices. Given a time series of returns, a Markov chain is defined by letting one state represent high returns and the other represent low returns. The random walk hypothesis restricts the transition probabilities of the Markov change to be equal irrespective of the prior years. Annual real returns are shown to exhibit significant nonrandom walk behavior in the sense that low (high) returns tend to follow runs of high (low) returns in the postwar period. Copyright 1991 by American Finance Association.

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Article provided by American Finance Association in its journal Journal of Finance.

Volume (Year): 46 (1991)
Issue (Month): 1 (March)
Pages: 239-63
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Handle: RePEc:bla:jfinan:v:46:y:1991:i:1:p:239-63

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  1. Spencer Thompson & Nathan Lead, 1999. "Modelling Share Price Behaviour Across Time," School of Economics and Finance Discussion Papers and Working Papers Series 071, School of Economics and Finance, Queensland University of Technology. [Downloadable!]
  2. N. Vijayamohanan Pillai, . "Causality and Error Correction in Markov Chain: Inflation in India Revisited," Working Papers id:743, esocialsciences.com. [Downloadable!]
  3. N. Vijayamohanan Pillai, 2004. "Causality and error correction in Markov chain: Inflation in India revisited," Centre for Development Studies, Trivendrum Working Papers 366, Centre for Development Studies, Trivendrum, India. [Downloadable!]
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This page was last updated on 2008-11-26.


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