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Testing for persistence in stock returns with GARCH-stable shocks

  • Prasad Bidarkota
  • J Huston Mcculloch

We investigate persistence in CRSP monthly excess stock returns, using a state space model with stable disturbances. The non-Gaussian state space model with volatility persistence is estimated by maximum likelihood, using the optimal filtering algorithm given by Sorenson and Alspach (1971 Automatica 7 465-79). The conditional distribution has a stable α of 1.89, and normality is strongly rejected even after accounting for GARCH. However, stock returns do not contain a significant mean-reverting component. The optimal predictor is the unconditional expectation of the series, which we estimate to be 9.8% per annum.

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Article provided by Taylor & Francis Journals in its journal Quantitative Finance.

Volume (Year): 4 (2004)
Issue (Month): 3 ()
Pages: 256-265

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Handle: RePEc:taf:quantf:v:4:y:2004:i:3:p:256-265
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