Detecting overreaction in the Bitcoin market: A quantile autoregression approach
Chevapatrakul, Thanaset; Mascia, Danilo V.
Danilo V. Mascia email@example.com
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|
|Peer Reviewed||Peer Reviewed|
|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|
|Keywords||JEL classification: C21; C51; C53; G00 Keywords: Bitcoin; cryptocurrencies; quantile regression; overreaction|
Detecting Overreaction In The Bitcoin Market
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