IDEAS home Printed from https://ideas.repec.org/a/ahs/journl/v9y2024i1p43-60.html
   My bibliography  Save this article

Calendar Anomalies in NFT Coins

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://dergipark.org.tr/tr/download/article-file/3549002
    Download Restriction: no
    File URL: https://libkey.io/10.30784/epfad.1393529?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kaiser, Lars, 2019. "Seasonality in cryptocurrencies," Finance Research Letters, Elsevier, vol. 31(C).
    2. 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.
    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.
    4. Kinateder, Harald & Papavassiliou, Vassilios G., 2021. "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, vol. 38(C).
    5. Aharon, David Yechiam & Qadan, Mahmoud, 2019. "Bitcoin and the day-of-the-week effect," Finance Research Letters, Elsevier, vol. 31(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen-Han Liu, 2024. "Exploring Calendar Effects in Bitcoin Returns: An Analysis of Market Efficiency," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(4), pages 1-3.
    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. Mueller, Lukas, 2024. "Revisiting seasonality in cryptocurrencies," Finance Research Letters, Elsevier, vol. 64(C).
    4. Shanaev, Savva & Ghimire, Binam, 2022. "A generalised seasonality test and applications for cryptocurrency and stock market seasonality," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 172-185.
    5. Algieri, Bernardina & Lawuobahsumo, Kokulo & Leccadito, Arturo, 2024. "Calendar Effects on Returns, Volatility and Higher Moments: Evidence from Crypto Markets," LIDAM Discussion Papers LFIN 2024001, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Chi, Yeguang & Hao, Wenyan, 2021. "Volatility models for cryptocurrencies and applications in the options market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    7. Rasim Özcan & Asad ul Islam KHAN & Sundas Iftikhar, 2024. "Whether The Cr Whether The Crypto Market Is Efficient? E et Is Efficient? Evidence F vidence From Testing The Validity Of The Efficient Market Hypothesis," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(1), pages 113-132, March.
    8. Long, Huaigang & Zaremba, Adam & Demir, Ender & Szczygielski, Jan Jakub & Vasenin, Mikhail, 2020. "Seasonality in the Cross-Section of Cryptocurrency Returns," Finance Research Letters, Elsevier, vol. 35(C).
    9. Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.
    10. Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
    11. Qadan, Mahmoud & Aharon, David Y. & Eichel, Ron, 2022. "Seasonal and Calendar Effects and the Price Efficiency of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 46(PA).
    12. Sonal Sahu & Alejandro Fonseca Ramírez & Jong-Min Kim, 2024. "Exploring Calendar Anomalies and Volatility Dynamics in Cryptocurrencies: A Comparative Analysis of Day-of-the-Week Effects before and during the COVID-19 Pandemic," JRFM, MDPI, vol. 17(8), pages 1-22, August.
    13. Aslanidis, Nektarios & Fernández Bariviera, Aurelio & Savva, Christos S., 2020. "Weekly dynamic conditional correlations among cryptocurrencies and traditional assets," Working Papers 2072/417680, Universitat Rovira i Virgili, Department of Economics.
    14. Kinateder, Harald & Papavassiliou, Vassilios G., 2021. "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, vol. 38(C).
    15. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    16. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.
    17. Christie Smith & Aaron Kumar, 2018. "Crypto‐Currencies – An Introduction To Not‐So‐Funny Moneys," Journal of Economic Surveys, Wiley Blackwell, vol. 32(5), pages 1531-1559, December.
    18. Guglielmo Maria Caporale & Alex Plastun, 2019. "Price overreactions in the cryptocurrency market," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1137-1155, August.
    19. Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022. "Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models," Finance Research Letters, Elsevier, vol. 49(C).
    20. Hu, Yang & Hou, Yang (Greg) & Oxley, Les & Corbet, Shaen, 2021. "Does blockchain patent-development influence Bitcoin risk?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ahs:journl:v:9:y:2024:i:1:p:43-60. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ersan Ersoy (email available below). General contact details of provider: https://epfjournal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.