This paper investigates the role of the frequency of price overreactions in the cryptocurrency market in the case of BitCoin over the period 2013-2018. Specifically, it uses a static approach to detect overreactions and then carries out hypothesis testing by means of a variety of statistical methods (both parametric and non-parametric) including ADF tests, Granger causality tests, correlation analysis, regression analysis with dummy variables, ARIMA and ARMAX models, neural net models, and VAR models. Specifically, the hypotheses tested are whether or not the frequency of overreactions (i) is informative about Bitcoin price movements (H1) and (ii) exhibits seasonality (H2). On the whole, the results suggest that it can provide useful information to predict price dynamics in the cryptocurrency market and for designing trading strategies (H1 cannot be rejected), whilst there is no evidence of seasonality (H2 is rejected).

中文翻译：

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比特币波动和价格过度反应的频率

本文以比特币为例，研究了 2013-2018 年期间价格过度反应频率在加密货币市场中的作用。具体来说，它使用静态方法检测过度反应，然后通过各种统计方法（参数和非参数）进行假设检验，包括 ADF 检验、格兰杰因果检验、相关分析、虚拟变量回归分析、ARIMA ARMAX 模型、神经网络模型和 VAR 模型。具体来说，测试的假设是过度反应的频率 (i) 是否能提供有关比特币价格变动的信息 (H1) 和 (ii) 是否表现出季节性 (H2)。总体上，