报告主题：Powerful Backtests for Historical Simulation Expected Shortfall Models

时间：2024年5月24日13:00-13:45

地点：腾讯会议 会议号：517 4242 8784  密码：6666

报告人：王旭慧

报告内容简介：

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.

主讲人简介：

王旭慧 上海立信会计金融学院 应用统计系

毕业于苏州大学统计学专业；研究领域：金融计量，投资组合；论文发表于《Journal of Business & Economic Statistics》和《Communications in Statistics - Theory and Methods》等期刊；参与国家自然科学基金项目以及狗熊会等多个横向课题。