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Quantile Correlations: Uncovering Temporal Dependencies In Financial Time Series

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  • THILO A. SCHMITT

    (Fakultät für Physik, Universität Duisburg-Essen, 47048 Duisburg, Germany)

  • RUDI SCHÄFER

    (Fakultät für Physik, Universität Duisburg-Essen, 47048 Duisburg, Germany)

  • HOLGER DETTE

    (Fakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, Germany)

  • THOMAS GUHR

    (Fakultät für Physik, Universität Duisburg-Essen, 47048 Duisburg, Germany)

Abstract

We conduct an empirical study using the quantile-based correlation function to uncover the temporal dependencies in financial time series. The study uses intraday data for the S&P500 stocks from the New York Stock Exchange (NYSE). After establishing an empirical overview, we compare the quantile-based correlation function to stochastic processes from the GARCH family and find striking differences. This motivates us to propose the quantile-based correlation function as a powerful tool to assess the agreements between stochastic processes and empirical data.

Suggested Citation

  • Thilo A. Schmitt & Rudi Schäfer & Holger Dette & Thomas Guhr, 2015. "Quantile Correlations: Uncovering Temporal Dependencies In Financial Time Series," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-16, November.
    • Handle: RePEc:wsi:ijtafx:v:18:y:2015:i:07:n:s0219024915500442
    DOI: 10.1142/S0219024915500442
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