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比特币极端收益波动的幂律标度

文章 arXiv papers · 作者: Stjepan Begušić et al.
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总结

该研究考察不同时间区间和数字资产交易所中比特币收益分布的尾部。研究检验共同标度行为并估计幂律指数，重点关注尾部是否意味着有限的二阶矩。作者报告称，在所考察的区间和交易所中，尾部均呈现缓慢衰减的幂律，渐近指数介于2与2.5之间。

作者将该指数解读为比特币收益的尾部比股票收益更厚的证据；股票收益的指数据称约为3，但比特币收益仍具有有限的二阶矩。这一发现支持在风险管理和投资组合优化中使用基于协方差的方法。摘要未提供样本日期、交易所名称、估计流程或不确定性范围，因此无法据此确定估计有多稳定，也无法判断报告的行为是否会在后续市场条件下持续。

核心观点

  • 研究考察了多个时间区间和数字资产交易所中的比特币收益。
  • 作者报告称，收益分布具有缓慢衰减的幂律尾部。
  • 估计的渐近指数介于2与2.5之间。
  • 报告的尾部比股票收益对应的尾部更厚。
  • 作者推断二阶矩有限，因此支持使用基于协方差的风险与投资组合方法。

标签

加密资产统计学波动率风险管理投资组合构建
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# Scaling properties of extreme price fluctuations in Bitcoin markets


# Scaling properties of extreme price fluctuations in Bitcoin markets









Detection of power-law behavior and studies of scaling exponents uncover the characteristics of complexity in many real world phenomena. The complexity of financial markets has always presented challenging issues and provided interesting findings, such as the inverse cubic law in the tails of stock price fluctuation distributions. Motivated by the rise of novel digital assets based on blockchain technology, we study the distributions of cryptocurrency price fluctuations. We consider Bitcoin returns over various time intervals and from multiple digital exchanges, in order to investigate the existence of universal scaling behavior in the tails, and ascertain whether the scaling exponent supports the presence of a finite second moment. We provide empirical evidence on slowly decaying tails in the distributions of returns over multiple time intervals and different exchanges, corresponding to a power-law. We estimate the scaling exponent and find an asymptotic power-law behavior with 2 < α < 2.5 suggesting that Bitcoin returns, in addition to being more volatile, also exhibit heavier tails than stocks, which are known to be around 3. Our results also imply the existence of a finite second moment, thus providing a fundamental basis for the usage of standard financial theories and covariance-based techniques in risk management and portfolio optimization scenarios.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。