Testing the martingale hypothesis for gross returns

Oliver Linton and Ekaterina Smetanina

Journal of Empirical Finance, 2016, vol. 38, issue PB, 664-689

Abstract: We propose an alternative ratio statistic for measuring predictability of stock prices. Our statistic is based on actual returns rather than logarithmic returns and is therefore better suited to capturing price predictability. It captures not only linear dependence in the same way as the variance ratio statistics of Lo and MacKinlay (1988) but also some nonlinear dependencies. We derive the asymptotic distribution of the statistics under the null hypothesis that simple gross returns are unpredictable after a constant mean adjustment. This represents a test of the weak form of the Efficient Market Hypothesis. We also consider the multivariate extension, in particular, we derive the restrictions implied by the EMH on multiperiod portfolio gross returns. We apply our methodology to test the gross return predictability of various financial series.

Keywords: Variance ratio tests; Martingale; Predictability (search for similar items in EconPapers)
JEL-codes: C10 C22 G10 G14 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:38:y:2016:i:pb:p:664-689

DOI: 10.1016/j.jempfin.2016.02.010

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