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Detecting overreaction in the Bitcoin market: A quantile autoregression approach

Chevapatrakul, Thanaset; Mascia, Danilo V.

Authors

Thanaset Chevapatrakul

Danilo V. Mascia danilo.mascia@nottingham.ac.uk



Abstract

We examine the persistence of returns on Bitcoin at different parts on the return distributions through the use of the quantile autoregressive (QAR) models. We find lower quantiles of the daily return distribution and upper quantiles of the weekly return distribution to exhibit positive dependence with past returns. The evidence points to overreaction in the Bitcoin market: investors overreact during days of sharp declines in the Bitcoin price and during weeks of market rallies.

Journal Article Type Article
Publication Date Sep 30, 2019
Journal Finance Research Letters
Print ISSN 1544-6123
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 30
Pages 371-377
APA6 Citation Chevapatrakul, T., & Mascia, D. V. (2019). Detecting overreaction in the Bitcoin market: A quantile autoregression approach. Finance Research Letters, 30, 371-377. https://doi.org/10.1016/j.frl.2018.11.004
DOI https://doi.org/10.1016/j.frl.2018.11.004
Keywords JEL classification: C21; C51; C53; G00 Keywords: Bitcoin; cryptocurrencies; quantile regression; overreaction
Publisher URL https://www.sciencedirect.com/science/article/pii/S1544612318305920

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