使用双从属莱维过程的比特币波动性和内在时间

IF 2 Q2 BUSINESS, FINANCE
Risks Pub Date : 2024-05-20 DOI:10.3390/risks12050082
Abootaleb Shirvani, Stefan Mittnik, William Brent Lindquist, Svetlozar Rachev
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引用次数: 0

摘要

我们提出了一个双隶属莱维过程--正态双反高斯(NDIG)--来模拟加密货币比特币的时间序列特性。通过使用两个从属过程,NDIG 既捕捉到了比特币收益的偏斜和肥尾特性,也捕捉到了驱动比特币收益的内在时间,并产生了一个无套利期权定价模型。在这一框架下,我们得出了两种比特币波动率测量方法。第一种是将 NDIG 期权定价与芝加哥期权交易所 VIX 模型相结合,计算隐含波动率;第二种是使用 NDIG 模型单位时间增量的波动率。这两种波动率测量方法都与基于历史标准差的波动率进行了比较。通过适当的线性缩放,NDIG 过程完美地捕捉到了观察到的样本波动率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bitcoin Volatility and Intrinsic Time Using Double-Subordinated Lévy Processes
We propose a doubly subordinated Lévy process, the normal double inverse Gaussian (NDIG), to model the time series properties of the cryptocurrency bitcoin. By using two subordinated processes, NDIG captures both the skew and fat-tailed properties of, as well as the intrinsic time driving, bitcoin returns and gives rise to an arbitrage-free option pricing model. In this framework, we derive two bitcoin volatility measures. The first combines NDIG option pricing with the Chicago Board Options Exchange VIX model to compute an implied volatility; the second uses the volatility of the unit time increment of the NDIG model. Both volatility measures are compared to the volatility based on the historical standard deviation. With appropriate linear scaling, the NDIG process perfectly captures the observed in-sample volatility.
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来源期刊
Risks
Risks Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
3.80
自引率
22.70%
发文量
205
审稿时长
11 weeks
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