预测Var的方法比较:Fhs与Evt方法

Panagiotis Delis, John Hlias Plikas
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引用次数: 1

摘要

金融机构多年来一直在寻求识别和处理金融工具投资组合中的市场风险的措施。在金融计量经济学文献中,VaR的预测受到了广泛的关注,即所谓的过滤历史模拟(FHS)和极值理论方法。本文通过结合方差条件模型的FHS和EVT方法,为一步超前VaR预测提供了方法上的贡献。在条件方差过程中计算不对称分布的投资组合回报,根据巴塞尔协议计算出准确的99%风险值预测。在计算VaR后,我们评估这些方法以呈现最合适的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing Methods to Forecasting Var: Fhs Versus Evt Approaches
Financial institutions have for many years sought measures, which identify and approach market risks in portfolios of financial instruments. Forecasting VaR has attracted a great deal of attention in the financial econometrics literature, the so-called filtered historical simulation (FHS) and Extreme Value Theory approaches. The paper provides a methodological contribution to the one-step-ahead VaR forecasting through some FHS and EVT approaches, which combine some conditional models for variance. Accounting asymmetrically distributed portfolio returns within the conditional variance process, accurate 99 per cent VaR forecasts are calculated for one-day-ahead horizon under Basel accords. After calculating VaR, we evaluate these methods for presenting the most appropriate methodology.
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