Forecasting day-ahead expected shortfall on the EUR/USD exchange rate: The (I)relevance of implied volatility

IF 6.9 2区 经济学 Q1 ECONOMICS
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引用次数: 0

Abstract

The existing literature provides mixed results on the usefulness of implied volatility for managing risky assets, while evidence for expected shortfall predictions is almost nonexistent. Given its forward-looking nature, implied volatility might be more valuable than backward-looking measures of realized price fluctuations. Conversely, the volatility risk premium embedded in implied volatility leads to overestimating the observed price variation. This paper explores the benefits of augmenting econometric models used in forecasting the expected shortfall, a risk measured endorsed in the Basel III Accord, with information on implied volatility obtained from EUR/USD option contracts. The day-ahead forecasts are obtained from several classes of econometric models: historical simulation, EGARCH, quantile regression-based HAR, joint VaR and ES model, and combination forecasts. We verify whether the resulting expected shortfall forecasts are well-specified and test the models’ accuracy. Our results provide evidence that the information provided by forward-looking implied volatility is more valuable than that in backward-looking realized measures. These results hold across multiple model specifications, are stable over time, hold under alternative loss functions, and are more pronounced during periods of higher market uncertainty when risk modeling matters most.

预测欧元/美元汇率的当日预期缺口:隐含波动率的(I)相关性
关于隐含波动率对管理风险资产的作用,现有文献提供的结果不一,而关于预期亏空 预测的证据几乎不存在。鉴于隐含波动率的前瞻性,它可能比已实现价格波动的后向衡量更有价值。相反,隐含波动率中蕴含的波动风险溢价会导致高估观察到的价格变化。本文探讨了利用从欧元/美元期权合约中获取的隐含波动率信息来增强用于预测预期缺口(《巴塞尔协议 III》认可的风险度量)的计量经济学模型的益处。日前预测从几类计量经济学模型中获得:历史模拟、EGARCH、基于量化回归的 HAR、VaR 和 ES 联合模型以及组合预测。我们验证了由此得出的预期亏空预测是否规范,并测试了模型的准确性。我们的研究结果证明,前瞻性隐含波动率提供的信息比后瞻性已实现波动率提供的信息更有价值。这些结果在多个模型规格中都成立,随着时间的推移而稳定,在其他损失函数下也成立,而且在市场不确定性较高、风险建模最重要的时期更为明显。
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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来源期刊
CiteScore
17.10
自引率
11.40%
发文量
189
审稿时长
77 days
期刊介绍: The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.
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