报告题目：Canonical Affine Stochastic Volatility Models
报告人： 李辰旭，北京大学光华管理学院教授
时间：10.17 星期四（16：00 – 17：30）
地点：新主楼 A618
讲座系列： 融 实
摘要:
We propose and implement "canonical affine stochastic volatility models" (CASVMs), which disentangle the fine structures and economic interpretations for multi-factor stochastic volatility of S&P500 index within affine framework. The factors explicitly consist of salient shape characteristics observable from, and latent ones unspanned by, (term structure of) VIX². The latter, termed as USV factors, inherently identify new risk resource(s), that are crucial for reconciling an empirical finding on incompleteness of volatility derivatives market excluding jumps, and more importantly for explaining, e.g., volatility dynamics and derivatives valuation. We demonstrate the substantial convenience in econometric analysis and superior empirical performance of CASVMs. For instance, the empirical results indicate that CASVMs with USV factors significantly outperform their counterparts without USV factors in fitting VIX²'s and squares of implied volatilities of options on VIX futures simultaneously, and, as shown in an example of comparison, improve the performance by 20.58% in sample and 29.38% out of sample. As an application, we quantitatively investigate on the puzzle of whether and how holding VIX call options instead of S&P500 put options truly benefits investors in hedging the downside risk of S&P500 index. This is the joint work with Haijian Guo, Yongxin Ye and Xin Zang.
汇报人简介：
李辰旭博士，北京大学光华管理学院教授，北京大学金融数学与金融工程研究中心主任，博士生导师。2004年获中国科学技术大学数学与应用数学学士学位，2010年获美国哥伦比亚大学博士学位。致力于金融计量经济学和金融工程学等领域的研究，多项研究成果发表在国际顶级的金融经济学、计量经济学、运筹学、统计学、数理金融学期刊上，包括Review of Financial Studies、Annals of Statistics、Journal of Business and Economic Statistics、Journal of Econometrics、Mathematics of Operations Research、Mathematical Finance等，其中三篇为独立作者发表。著有《金融中的数学方法》（于2021年1月由北京大学出版社出版，属光华思想力书系)。担任学术期刊《系统工程理论与实践》编委和学术期刊《经济管理学刊》数据科学与人工智能方向副主编（Associate Editor）。曾获由国际工业与系统工程学会（The Institute of Industrial and Systems Engineers）颁发的IIE Transactions运筹学最佳论文奖“2018 Operations Engineering and Analytics Best Paper Award”、全国第七届教育部高等学校科学研究优秀成果奖（人文社会科学）等。
