近日，我院裴沛副教授的论文“Powerful Backtests for Historical Simulation Expected Shortfall”在统计学与计量经济学国际权威期刊Journal of Business & Economic Statistics（中财AAA类）接受发表。该论文的合作者为复旦大学杜在超教授、上海立信会计金融学院王旭慧老师和山东大学杨涛老师。

论文摘要：

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.

作者介绍：

裴沛，美国印第安纳大学布鲁明顿分校经济学博士，现任中央财经大学创新发展学院中国金融发展研究院长聘副教授，主要研究领域包括金融计量经济学、宏观计量经济学、金融风险管理等，在Journal of Business and Economic Statistics, Journal of Banking and Finance, Journal of Time Series Analysis, Macroeconomic Dynamics, Journal of Macroeconomics等国际期刊发表论文。

期刊简介：

Journal of Business and Economic Statistics(JBES)自1983年以来由美国统计协会每季度出版一次，隶属于TAYLOR & FRANCIS出版公司。它是应用经济学家，计量经济学家和统计学家的独特聚会之所，为商业和经济学的广泛主题开发适当的实证方法。JBES覆盖范围包括预测，数据质量，政策评估，实证经济学，金融，市场营销等所有主题。出版通常需要对方法学作出重大贡献和实质性的实际应用。JBES也将在计算，模拟，网络和图形领域发表文章，只要预期的应用与期刊感兴趣的一般主题密切相关。

文章链接：https://doi.org/10.1080/07350015.2023.2252881