Dynamic analysis of calendar anomalies in cryptocurrency markets: evidences of adaptive market hypothesis

This paper analyses the effects known as the day of the week and the month of the year in the cryptocurrency markets. The closing values of eleven cryptocurrencies have been considered. The study employs dummy variable regression techniques, ANOVA and Friedman tests for assessing two calendar anomalies, the day-of-week and month-of-year effects. To test these calendar effects, we have applied both full sample and rolling-regression techniques for two lengths of the rolling sample intervals. Furthermore, we have examined the existence of long memory in day-of-the- week and month-of-the-year cryptocurrency returns. The results provide evidence about the existence of day-of-the-week and month-of-the-year effects in cryptocurrency returns, in particular, on Thursdays and in November. In addition, it should be added that the general results of the current study show that the calendar effect in the cryptocurrency market is dynamic rather than static, which indicates that the calendar effect is a phenomenon that varies over time.