The Ashley and Patterson (1986) test for serial independence in daily stock returns, revisited

Richard A. Ashley () and Faezeh Najafi ()
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Richard A. Ashley: Virginia Tech
Faezeh Najafi: Virginia Tech

Annals of Operations Research, 2025, vol. 346, issue 1, No 28, 567-584

Abstract: Abstract We update and extend the non-parametric test proposed in Ashley and Patterson (J Financ Quant Anal 21:221–227, 2014) – of the proposition that the (pre-whitened) daily stock returns for a firm are serially independent, and hence unpredictable from their own past. That paper applied this test to daily returns from 1962 to 1981 for several U.S. corporations and aggregate indices, finding mixed evidence against this null hypothesis of serial independence. The returns dataset is updated here to include thirteen firms which are currently more relevant, and the sample is extended through the end of 2023. We also update the simulation methodology here to properly account for the conditional heteroskedasticity in the daily returns data, so that the present results should now be more statistically reliable. The results are broadly in line with our earlier results, but they do suggest further avenues of research in this area.

Keywords: Stock returns; Random walks; Serial independence; Bootstrap; Nonparametric testing; Serial independence (search for similar items in EconPapers)
JEL-codes: C18 C22 C31 C51 C52 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-024-06355-0

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