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Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach

Author

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  • Sungro Lee, Chang Sik Kim, In-Moo Kim

    (Sungkyunkwan University, Sungkyunkwan University, Sungkyunkwan University)

  • Chang Sik Kim

    (Sungkyunkwan University)

  • In-Moo Kim

    (Sungkyunkwan University)

Abstract

This paper employs a new testing procedure for detecting the presence of Monday effects using high-frequency intraday data. Our approach to test the Monday effect is based on spatial dominance, which enables us to analyze the expected sum of instantaneous utilities during trading hours by considering the intraday patterns of returns. The testing of the methods used in previous studies compares the expected utilities only at a specific time, usually market closing time. Empirical results from our tests provide strong evidence of the Monday effect for the 1983 to 1987 period. We also find that the Monday effect is driven by large negative returns accrued during early Monday mornings, The conventional analyses for the Monday effect, such as regression analysis and stochastic dominance, cannot provide strong evidence of the Monday effect for the same period because these testing methods do not consider the return behavior during Monday mornings.

Suggested Citation

  • Sungro Lee, Chang Sik Kim, In-Moo Kim & Chang Sik Kim & In-Moo Kim, 2012. "Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach," Korean Economic Review, Korean Economic Association, vol. 28, pages 69-90.
    • Handle: RePEc:kea:keappr:ker-20120630-28-1-04
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    efficient markets; high-frequency intraday returns; spatial dominance; subsampling; the Monday effect;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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