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Calendar Anomalies in NFT Coins

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  • Zeliha Can Ergün

Abstract

This study examines the effect of day-of-the-week, month-of-the-year, and turn-of-the-month anomalies on NFT coins (Stacks, Tezos, and Decentraland) and Bitcoin. To this end, the generalized autoregressive conditional heteroscedasticity (GARCH) model was employed over the period 2019–2023. Based on the day-of-the-week anomaly results, Bitcoin has lower returns on Thursdays and Fridays, and Stacks has lower returns on Wednesdays. The remaining coins do not exhibit that anomaly. According to the month-of-the-year effect results, all evaluated coins generate abnormal returns in January. Moreover, positive returns are also reported in February for Tezos, Decentraland, and Bitcoin. Additionally, Bitcoin has positive returns in March as well. Furthermore, besides January, Stacks has significantly positive returns in April and May. Finally, the results of the turn-of-the-month anomaly suggest that only Stacks has statistically significant and positive returns on the last day of the month and the next three days. The remaining cryptocurrencies do not have such an anomaly. Overall, the findings of this study suggest the existence of calendar anomalies in the cryptocurrency market that contradict the assumptions of market efficiency. By using these outcomes, investors may develop trading strategies for their portfolio selection; hence, by taking advantage of the market, they could earn unusual profits.

Suggested Citation

  • Zeliha Can Ergün, 2024. "Calendar Anomalies in NFT Coins," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 9(1), pages 43-60.
    • Handle: RePEc:ahs:journl:v:9:y:2024:i:1:p:43-60
    DOI: 10.30784/epfad.1393529
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    References listed on IDEAS

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    1. Yutaka Kurihara & Akio Fukushima, 2017. "The Market Efficiency of Bitcoin: A Weekly Anomaly Perspective," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(3), pages 1-4.
    2. 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.
    3. Kinateder, Harald & Papavassiliou, Vassilios G., 2021. "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, vol. 38(C).
    4. Kaiser, Lars, 2019. "Seasonality in cryptocurrencies," Finance Research Letters, Elsevier, vol. 31(C).
    5. Aharon, David Yechiam & Qadan, Mahmoud, 2019. "Bitcoin and the day-of-the-week effect," Finance Research Letters, Elsevier, vol. 31(C).
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    More about this item

    Keywords

    Calendar Anomalies; Efficient Markets; Cryptocurrencies;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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