Seasonality, Trend-following, and Mean reversion in Bitcoin

16 Pages Posted: 27 Apr 2022

See all articles by Matus Padysak

Matus Padysak

Comenius University - Faculty of Mathematics, Physics and Informatics; Quantpedia.com

Radovan Vojtko

Quantpedia.com

Date Written: April 11, 2022

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

Suggested Citation

Padyšák, Matúš and Padyšák, Matúš and Vojtko, Radovan, Seasonality, Trend-following, and Mean reversion in Bitcoin (April 11, 2022). Available at SSRN: https://ssrn.com/abstract=4081000 or http://dx.doi.org/10.2139/ssrn.4081000

Matúš Padyšák (Contact Author)

Comenius University - Faculty of Mathematics, Physics and Informatics

Mlynská dolina
SK-842 48 Bratislava, Bratislava 842 48
Slovakia

Quantpedia.com ( email )

Dulovo namestie 14
Bratislava, 85110
Slovakia

Radovan Vojtko

Quantpedia.com ( email )

Dulovo namestie 14
Bratislava, 85110
Slovakia

HOME PAGE: http://www.quantpedia.com

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