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The intraday directional predictability of large Australian stocks: A cross-quantilogram analysis

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  • Todorova, Neda

Abstract

This study investigates the directional predictability of overnight periods for intraday returns of large Australian stocks. The intraday reactions to overnight developments are studied using cross-quantilograms, a new, flexible methodology that facilitates detailed insights into the quantile dependence between two time series. The results provide evidence for the existence of intraday reversals after overnight periods that carry very bad news, whereas the picture of the short-term reactions to very positive overnight returns is mixed. The observed rebounds concern extreme quantiles and occur with a short delay during the first part of the trading day. The study also shows that continuation and reversal effects are not mutually exclusive. The economic significance of the identified patterns is illustrated by analysing the performance of a simple contrarian strategy.

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  • Todorova, Neda, 2017. "The intraday directional predictability of large Australian stocks: A cross-quantilogram analysis," Economic Modelling, Elsevier, vol. 64(C), pages 221-230.
    • Handle: RePEc:eee:ecmode:v:64:y:2017:i:c:p:221-230
    DOI: 10.1016/j.econmod.2017.03.022
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    10. Narayan, Paresh Kumar & Liu, Ruipeng, 2018. "A new GARCH model with higher moments for stock return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 93-103.
    11. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
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    19. Urom, Christian & Abid, Ilyes & Guesmi, Khaled & Chevallier, Julien, 2020. "Quantile spillovers and dependence between Bitcoin, equities and strategic commodities," Economic Modelling, Elsevier, vol. 93(C), pages 230-258.
    20. Jing Wan & Shen Zhang & Xu Feng, 2024. "How does the stock market affect the interest rate corridor system in China?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1820-1833, April.
    21. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    22. Cho, Dooyeon & Han, Heejoon, 2021. "The tail behavior of safe haven currencies: A cross-quantilogram analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).

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    More about this item

    Keywords

    Quantile dependence; Directional predictability; Reversals; Australian stock market;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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