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Tests for Abnormal Returns in the Presence of Event-Induced Cross-Sectional Correlation

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  • Niklas Ahlgren
  • Jan Antell

Abstract

We introduce a spatial autoregressive model for cross-sectional correlation of abnormal returns. In the model the abnormal returns of firms in the same industry are correlated, whereas the abnormal returns of firms in different industries are uncorrelated. Tests for abnormal returns which are robust to event-induced cross-sectional correlation are proposed. We apply our tests to U.S. stock returns from Bear Stearns’ collapse and Lehman Brothers’ bankruptcy in 2008. We document evidence of event-induced cross-sectional correlation. Simulations show that tests which estimate the cross-sectional correlation from the event period have size close to the nominal level.

Suggested Citation

  • Niklas Ahlgren & Jan Antell, 2017. "Tests for Abnormal Returns in the Presence of Event-Induced Cross-Sectional Correlation," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 286-301.
    • Handle: RePEc:oup:jfinec:v:15:y:2017:i:2:p:286-301.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbw012
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    References listed on IDEAS

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    1. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
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    5. Kelejian, Harry H. & Piras, Gianfranco, 2011. "An extension of Kelejian's J-test for non-nested spatial models," Regional Science and Urban Economics, Elsevier, vol. 41(3), pages 281-292, May.
    6. Kolari, James W. & Pynnonen, Seppo, 2011. "Nonparametric rank tests for event studies," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 953-971.
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    Cited by:

    1. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.

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    More about this item

    Keywords

    abnormal return; cross-sectional correlation; event study; spatial autoregressive model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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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