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Dynamic cross-autocorrelation in stock returns

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  • Kinnunen, Jyri

Abstract

I investigate whether the cross-autocorrelation pattern of US small- and large-firm returns changes with the variance of returns using an exponential vector autoregressive model with volatility. The model allows the testing of dynamic cross-autocorrelation effects, while controlling for own time-varying autoregressive coefficients. Using daily and weekly data from 1965 to 2015, a constant cross-autocorrelation pattern is rejected. Returns on a large-firm portfolio are found to lead returns on a small-firm portfolio. The lead-lag relation changes over time with the variance of the large-firm returns. Traditional vector autoregressions with constant cross-autoregressive coefficients appear to be overly restrictive when testing lead-lag relations in stock markets.

Suggested Citation

  • Kinnunen, Jyri, 2017. "Dynamic cross-autocorrelation in stock returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 162-173.
  • Handle: RePEc:eee:empfin:v:40:y:2017:i:c:p:162-173
    DOI: 10.1016/j.jempfin.2016.08.005
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    References listed on IDEAS

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    More about this item

    Keywords

    Autocorrelation; Cross-autocorrelation; Volatility; Vector autoregressive model; Exponential autoregressive model;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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