Seasonality, Trend-following, and Mean reversion in Bitcoin

Abstract

The cryptocurrency market is not negligible nor minor anymore. With the continuous development of the crypto market, researchers aimed to analyze novel cryptocurrencies thoroughly. An excellent starting point might be in other recognized effects from the developed asset classes. This research examines seasonality effects such as when the major NYSE opened or closed and their intraday, overnight, or daily components. Furthermore, we also examine the distribution of the daily returns and the returns that are significant. The results point to a simple seasonality strategy that is based on holding BTC only for two hours per day. The second aim is to examine trend-following and mean reversion strategies. The data suggests that BTC tends to trend when it is at its maximum and bounce back when at the minimum. These findings support the empirical observations that BTC tends to trend strongly and revert after drawdowns.

Keywords: Bitcoin, trend-following, mean reversion, seasonality, trading strategy