Bitcoin’s Weekend Effect: Returns, Volatility, and Volume (2014–2024)

Using daily BTC-USD data from September 19, 2014 to January 21, 2024, this paper re-examines whether weekends differ from weekdays for Bitcoin along three margins: average returns, close-to-close volatility, and trading activity. We implement Welch mean comparisons and HAC-robust OLS with month fixed effects (bandwidths 5, 7, and 14). In the full sample and across subsamples (2016–2019; 2020–2023; early 2024), we find no detectable weekend–weekday gap in average returns, while volatility and trading activity are lower on weekends. The patterns are robust to using squared returns as a volatility proxy. The joint evidence is consistent with liquidity and attention mechanisms—quieter weekends rather than compensating return premia. Replication files reproduce all tables and figures.

Authors

Institutions

Publication Details

Journal
Proceedings of Business and Economic Studies
Published
2025-10-03
DOI
https://doi.org/10.26689/pbes.v8i5.11691
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bitcoin’s Weekend Effect: Returns, Volatility, and Volume (2014–2024)

Zhe Xu
Proceedings of Business and Economic Studies
Blockchain Technology Applications and Security
article

Bitcoin’s Weekend Effect: Returns, Volatility, and Volume (2014–2024)

Zhe Xu
article en

Abstract

Using daily BTC-USD data from September 19, 2014 to January 21, 2024, this paper re-examines whether weekends differ from weekdays for Bitcoin along three margins: average returns, close-to-close volatility, and trading activity. We implement Welch mean comparisons and HAC-robust OLS with month fixed effects (bandwidths 5, 7, and 14). In the full sample and across subsamples (2016–2019; 2020–2023; early 2024), we find no detectable weekend–weekday gap in average returns, while volatility and trading activity are lower on weekends. The patterns are robust to using squared returns as a volatility proxy. The joint evidence is consistent with liquidity and attention mechanisms—quieter weekends rather than compensating return premia. Replication files reproduce all tables and figures.

Proceedings of Business and Economic StudiesVol. 8(5)
Zhengzhou University (CN), Zhengzhou University of Science and Technology (CN)
Openalex Percentile: Top 58%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.