主题：Predicting the VIX and the Volatility Risk Premium: What’s Credit and Commodity Volatility Risk Got To Do With It? （预测VIX和波动风险溢价：信用和大宗商品波动风险与之有何关系？）
主讲人：Eric Ghysels，北卡罗来纳大学教堂山分校经济学与金融学教授
日期：2014年11月5日（周三）
时间：下午1:30-3:00
地点：德州扑克大小
金融德州扑克大小
4号楼101教室
语言：英文
摘要：
This paper presents an innovative approach to extracting factors which are shown to predict the VIX, the S&P 500 Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we extract factors from panels of filtered volatilities - in particular large panels of univariate financial asset ARCH-type models and (2) we price equity volatility risk using factors which go beyond the equity class. These are volatility factors extracted from panels of volatilities of short-term funding and long-run corporate spreads as well as volatilities of energy and metals commodities returns and sport/future spreads.
主讲人简介:
Eric Ghysels is the Bernstein Distinguished Professor of Economics at the University of North Carolina - Chapel Hill and Professor of Finance at the Kenan-Flagler Business School. His main research interests are time series econometrics and finance. He obtained his Ph.D. from the Kellogg Graduate School of Management at Northwestern University. He has been a visiting professor or scholar at several major U.S., European and Asian universities. He gave invited lectures, including at the World Congress of the Econometric Society, the American Statistical Association Meetings, several (EC)2 Conferences, among many others. He serves on the editorial boards of several academic journals and was co-editor of the Journal of Business and Economic Statistics (2000-2003) and is currently co-editor of the Journal of Financial Econometrics. He has published in the leading economics, finance and statistics journals and has published several books. He is a fellow of the American Statistical Association and The Journal of Econometrics. He is also the Founding Co-President of the Society for Financial Econometrics (SoFiE).
