Bitcoin Time-of-Day, Day-of-Week and Month-of-Year Effects in Returns and Trading Volume

Research output: Working paper

Abstract

There is a large literature that reports time-specific anomalies in equity markets such as the Monday effect, the January effect and the Halloween effect. This study is the first to report intra-day time-of-day, day-of-week, and month-of-year effects for Bitcoin returns and trading volume. Using more than 15 million price and trading volume observations from seven global Bitcoin exchanges reveal time-varying effects but no consistent or persistent patterns across the sample period. The results suggest that Bitcoin markets are efficient.
Original languageEnglish
Publication statusPublished - 17 Dec 2017

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Trading volume
Time-varying
Equity markets
January effect
Monday effect
Anomaly

Cite this

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title = "Bitcoin Time-of-Day, Day-of-Week and Month-of-Year Effects in Returns and Trading Volume",
abstract = "There is a large literature that reports time-specific anomalies in equity markets such as the Monday effect, the January effect and the Halloween effect. This study is the first to report intra-day time-of-day, day-of-week, and month-of-year effects for Bitcoin returns and trading volume. Using more than 15 million price and trading volume observations from seven global Bitcoin exchanges reveal time-varying effects but no consistent or persistent patterns across the sample period. The results suggest that Bitcoin markets are efficient.",
author = "Dirk Baur and Daniel Cahill and Keith Godfrey and Zhangxin Liu",
year = "2017",
month = "12",
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AU - Liu, Zhangxin

PY - 2017/12/17

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AB - There is a large literature that reports time-specific anomalies in equity markets such as the Monday effect, the January effect and the Halloween effect. This study is the first to report intra-day time-of-day, day-of-week, and month-of-year effects for Bitcoin returns and trading volume. Using more than 15 million price and trading volume observations from seven global Bitcoin exchanges reveal time-varying effects but no consistent or persistent patterns across the sample period. The results suggest that Bitcoin markets are efficient.

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