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Another Look at Calendar Anomalies

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  • Evanthia Chatzitzisi

    (Department of Economics, University of Macedonia, Greece)

  • Stilianos Fountas

    (Department of Economics, University of Macedonia, Greece)

  • Theodore Panagiotidis

    (Department of Economics, University of Macedonia, Greece; Rimini Centre for Economic Analysis)

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.

Suggested Citation

  • Evanthia Chatzitzisi & Stilianos Fountas & Theodore Panagiotidis, 2019. "Another Look at Calendar Anomalies," Working Paper series 19-07, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:19-07
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    3. 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.
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    Keywords

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