光华讲坛——社会名流与企业家论坛第 5608期

主题：Spectral backtests of forecast distributions with application to risk management（预测分布的频谱回溯测试及其在风险管理中的应用）

主讲人：英国约克大学 Alexander McNeil 教授

主持人：西南财经大学经济与管理研究院  黄霖教授

时间：2019年11月20日（周三）上午10:00—11:30

地点：西南财经大学柳林校区格致楼1211会议室

主办单位：经济与管理研究院  科研处

主讲人简介：

Alexander McNeil has been Professor of Actuarial Science at the University of York since September 2016. Educated at Imperial College London and Cambridge University, he was formerly Assistant Professor in the Department of Mathematics at ETH Zurich and Maxwell Professor of Mathematics in the Department of Actuarial Mathematics and Statistics at Heriot-Watt University. He founded and led the Scottish Financial Risk Academy (SFRA) between 2010 and 2016.

His research interests lie in the development of quantitative methodology for financial risk management and include models for market, credit and insurance risks, financial time series analysis, models for extreme risks and correlated risks and enterprise-wide models for solvency and capital adequacy. He has published papers in leading actuarial, statistics, econometrics and financial mathematics journals and is a regular speaker at international risk management conferences.

He is joint author, together with Rüdiger Frey and Paul Embrechts, of the book "Quantitative Risk Management: Concepts, Techniques and Tools", published by Princeton University Press (2005/2015). He is also an Honorary Fellow of the Institute and Faculty of Actuaries and a Corresponding Member of the Swiss Association of Actuaries.

Alexander McNeil约克大学精算学教授。他在伦敦帝国理工学院和剑桥大学分别取得学士和博士学位，曾任苏黎世联邦理工学院数学系助理教授和赫瑞瓦特大学精算数学和统计系麦克斯韦尔数学教授。他的研究兴趣在研究金融风险管理的定量方法，包括市场、信用和保险风险模型、金融时间序列分析、极值风险和相关风险模型，以及偿付能力和资本充足性的全企业模型。他的论文主要发表在精算、统计学、计量经济学和金融数学等期刊上。他与Rüer Frey和Paul Embrechts合著了《定量风险管理：概念、技术和工具》(2005/2015年，普林斯顿大学出版社出版)。他也是瑞士精算师学院的荣誉研究员和瑞士精算师协会的会员。

内容提要：

We study a class of backtests for forecast distributions in which the test statistic depends on a spectral transformation that weights exceedance events by a function of the modeled probability level. The weighting scheme is specified by a kernel measure which makes explicit the user’s priorities for model performance. The class of spectral backtests includes tests of unconditional coverage and tests of conditional coverage. We show how the class embeds a wide variety of backtests in the existing literature, and further propose novel variants which are easily implemented, well-sized and have good power. In an empirical application, we backtest forecast distributions for the overnight P&L of ten bank trading portfolios. For some portfolios, test results depend materially on the choice of kernel.

文章研究了一类针对预测分布的回测，其中测试统计量取决于频谱变换，该频谱变换通过建模的概率水平对超出事件进行加权。加权方案由核度量指定。 该类频谱回测包括无条件覆盖测试和有条件覆盖测试。文章将展示该类回测，如何包含了现有文献中讨论过的各种各样的回测，并进一步提出易于实现，大小合适且具有强大功能的新方法。在实证应用中，我们回溯了十个银行交易账户的隔夜损益的预测分布。我们发现，对于某些产品组合，测试结果在很大程度上取决于内核的选择。