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Another Look at Calendar Anomalies

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Abstract

We employ daily aggregate and sectoral S&P500 data to shed further light on the day-of-the-week anomaly using GARCH and EGARCH models. We obtain the following results: First, there is strong evidence for day-of-the-week effects in all sectors, implying that these effects are part of a wide phenomenon affecting the entire market structure. Second, using rolling-regressions, we find that significant seasonality represents a small proportion of the total sample. Third, using a logit setup, we examine the impact of four factors, namely recessions, uncertainty, trading volume and bearish sentiment on seasonality. We reveal that recessions and uncertainty have explanatory power for anomalies whereas trading volume does not.

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  • Evanthia Chatzitzisi & Stilianos Fountas & Theodore Panagiotidis, 2019. "Another Look at Calendar Anomalies," Discussion Paper Series 2019_02, Department of Economics, University of Macedonia, revised Feb 2019.
    • Handle: RePEc:mcd:mcddps:2019_02
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    Cited by:

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    2. Iordanis Petsas & Fengyun Li & Jinghan Cai, 2023. "Work, leisure, and the Monday Blue: Does culture matter?," Economics and Business Letters, Oviedo University Press, vol. 12(3), pages 203-212.
    3. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    4. Chhabra, Damini & Gupta, Mohit, 2022. "Calendar anomalies in commodity markets for natural resources: Evidence from India," Resources Policy, Elsevier, vol. 79(C).
    5. Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.
    6. Adefemi A. OBALADE & Akona TSHUTSHA & Lungelo MVUYANA & Nothando NDLOVU & Paul-Francois MUZINDUTSI, 2022. "Are Frontier African Markets Inefficient or Adaptive? Application of Rolling GARCH Models," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 6(1), pages 19-35.
    7. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    8. Kenourgios, Dimitris & Samios, Yiannis, 2021. "Halloween effect and active fund management," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 534-544.
    9. Khushboo Aggarwal & Mithilesh Kumar Jha, 2023. "Stock returns seasonality in emerging asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(1), pages 109-130, March.
    10. Valadkhani, Abbas & O'Mahony, Barry, 2024. "Sector-specific calendar anomalies in the US equity market," International Review of Financial Analysis, Elsevier, vol. 95(PA).

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    More about this item

    Keywords

    day-of-the-week effect; GARCH; calendar anomalies; S&P500 Index; sectors; rolling regression; logit.;
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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