预测比特币风险措施:一种稳健的方法

Carlos Trucíos
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引用次数: 73

摘要

在过去的几年里,比特币和其他加密货币吸引了许多投资者、从业者和研究人员的兴趣。然而,很少有人注意到其风险措施的可预测性。本文使用几种波动率模型比较了比特币的一步前波动率和风险价值的可预测性。我们还包括考虑异常值存在的程序,并以稳健的方式估计波动性和风险价值。我们的研究结果表明,在预测波动率和估计风险价值时,鲁棒程序优于非鲁棒程序。这些结果表明,异常值的存在在比特币风险度量的建模和预测中起着重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Bitcoin Risk Measures: A Robust Approach
Abstract Over the last few years, Bitcoin and other cryptocurrencies have attracted the interest of many investors, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. This paper compares the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk in a robust fashion. Our results show that robust procedures outperform non-robust ones when forecasting the volatility and estimating the Value-at-Risk. These results suggest that the presence of outliers plays an important role in the modelling and forecasting of Bitcoin risk measures.
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