一、主题：Understanding Common Risk Factors in Variance Swap Rates, Market Return Predictability and Variance Swap Investments When Volatility can Jump
二、主讲人：金星，英国华威大学商学院金融副教授。美国马里兰大学Smith商学院管理科学与统计博士毕业。主要研究领域：资产定价、衍生品、投资组合、风险管理与金融工程。金星教授的研究成果发表在Review of Financial Studies、Management Science、Mathematical Finance, Finance and Stochastics, Journal of Banking and Finance, Journal of Economic Dynamics and Control, Journal of Mathematics Economics等国外金融与经济高水平期刊上。
Abstract: This paper proposes a tractable self-exciting double-jump model for stock return and its variance processes, extending existing two-factor term structure models of variance swap rates in the literature to a new three-factor model. Various goodness-of-fit tests show that our three-factor model outperforms the two-factor model in fitting the S&P 500 return and its variance swap rates. More importantly, we show that the expected log market excess return is linearly related to variance rates, suggesting a novel predictive regression model for the market returns. In stark contrast to the existing literature, our empirical results demonstrate that variance swap rates have superior predictive ability compared with variance risk premiums (VRPs) for predicting market returns both in-sample and out-of-sample for horizons up to two years. Unlike the popular double-jump model in the literature, our new model allows us to solve the optimal variance swap investment in a semi-closed form which greatly facilitates new understanding of volatility trading. Specifically, we find that the investor always takes a long-short-long strategy in investing variance swaps, and incurs sizeable economic loss caused by both model and parameter misspecifications.