Version 1
: Received: 13 May 2024 / Approved: 13 May 2024 / Online: 14 May 2024 (11:14:11 CEST)
How to cite:
Sahu, S.; Ramírez, A. F.; Kim, J.-M. A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market. Preprints2024, 2024050905. https://doi.org/10.20944/preprints202405.0905.v1
Sahu, S.; Ramírez, A. F.; Kim, J.-M. A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market. Preprints 2024, 2024050905. https://doi.org/10.20944/preprints202405.0905.v1
Sahu, S.; Ramírez, A. F.; Kim, J.-M. A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market. Preprints2024, 2024050905. https://doi.org/10.20944/preprints202405.0905.v1
APA Style
Sahu, S., Ramírez, A. F., & Kim, J. M. (2024). A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market. Preprints. https://doi.org/10.20944/preprints202405.0905.v1
Chicago/Turabian Style
Sahu, S., Alejandro Fonseca Ramírez and Jong-Min Kim. 2024 "A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market" Preprints. https://doi.org/10.20944/preprints202405.0905.v1
Abstract
This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
