Good Volatility, Bad Volatility, and the Cross Section of Cryptocurrency Returns

Zehua Zhang, Ran Zhao
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引用次数: 1

Abstract

This paper examines the distributional properties of cryptocurrency realized variation measures (RVM) and the predictability of RVM on future returns. We show the cryptocurrency volatility persistence and the importance of the asymmetry on volatility forecasting. Signed jumps variations contribute around 18% of the cryptocurrency return quadratic variations. The realized signed jump (RSJ) strongly predicts the cross-sectional future excess returns. Sorting the cryptocurrencies into portfolios sorted by RSJ yields statistically and economically significant differences in future excess returns. This jump risk premium remains significant after controlling for cryptocurrency market characteristics and existing risk factors. The standard cross-sectional regression convinces the cryptocurrency return predictability from RSJ by controlling multiple cryptocurrency characteristics. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.
好的波动性,坏的波动性,以及加密货币回报的横截面
本文研究了加密货币已实现变化度量(RVM)的分布特性以及RVM对未来收益的可预测性。我们展示了加密货币波动性的持久性和不对称性对波动性预测的重要性。符号跳跃变化约占加密货币回报二次变化的18%。已实现的符号跳升(RSJ)强有力地预测了横断面未来超额收益。根据RSJ将加密货币分类为投资组合,未来的超额回报在统计上和经济上都存在显著差异。在控制了加密货币市场特征和现有风险因素后,这种跳跃风险溢价仍然很大。标准的横截面回归通过控制多个加密货币特征来确信RSJ的加密货币返回可预测性。投资者的关注解释了未来加密货币回报中实现跳跃风险的可预测性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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