近日，我院裴沛副教授的論文“Powerful Backtests for Historical Simulation Expected Shortfall”在統計學與計量經濟學國際權威期刊Journal of Business & Economic Statistics（中财AAA類）接受發表。該論文的合作者為複旦大學杜在超教授、上海立信會計金融學院王旭慧老師和山東大學楊濤老師。

論文摘要：

Since 2016, the Basel Committee on Banking Supervision has regulated banks to switch from a Value-at-Risk (VaR) to an Expected Shortfall (ES) approach to measuring the market risk and calculating the capital requirement. In the transition from VaR to ES, the major challenge faced by financial institutions is the lack of simple but powerful tools for evaluating ES forecasts (i.e., backtesting ES). This article first shows that the unconditional backtest is inconsistent in evaluating the most popular Historical Simulation (HS) and Filtered Historical Simulation (FHS) ES models, with power even less than the nominal level in large samples. To overcome this problem, we propose a new class of conditional backtests for ES that are powerful against a large class of alternatives. We establish the asymptotic properties of the tests, and investigate their finite sample performance through some Monte Carlo simulations. An empirical application to stock indices data highlights the merits of our method.

作者介紹：

裴沛，美國印第安納大學布魯明頓分校經濟學博士，現任韦德体育bevictor中國金融發展研究院長聘副教授，主要研究領域包括金融計量經濟學、宏觀計量經濟學、金融風險管理等，在Journal of Business and Economic Statistics, Journal of Banking and Finance, Journal of Time Series Analysis, Macroeconomic Dynamics, Journal of Macroeconomics 等國際期刊發表論文。

期刊簡介：

Journal of Business and Economic Statistics(JBES) 自1983年以來由美國統計協會每季度出版一次，隸屬于TAYLOR & FRANCIS出版公司。它是應用經濟學家，計量經濟學家和統計學家的獨特聚會之所，為商業和經濟學的廣泛主題開發适當的實證方法。JBES覆蓋範圍包括預測，數據質量，政策評估，實證經濟學，金融，市場營銷等所有主題。出版通常需要對方法學作出重大貢獻和實質性的實際應用。JBES也将在計算，模拟，網絡和圖形領域發表文章，隻要預期的應用與期刊感興趣的一般主題密切相關。

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https://doi.org/10.1080/07350015.2023.2252881