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狗万app講座:Information Content of Aggregate Implied Volatility Spread

狗万appSBF論壇2019年第22講

講座題目:Information Content of Aggregate Implied Volatility Spread

時間:7月16日(週二) 10:30-11:30

地點:博學樓925

主講人:韓冰

主講人簡介:

韓冰教授現任多倫多大學羅特曼管理狗万滚球金融學教授 。韓教授在加利福尼亞大學洛杉磯分校和芝加哥大學分別取得金融學博士學位(2002)和數學博士學位(1997)。韓教授的主要研究領域是投資和行爲金融學 。他的論文發表在頂級金融學,經濟學和管理學雜誌上,包括Journal of Finance, Journal of Financial Economics ,Review of Financial Studies, Review of Economic Studies ,Journal of Economic Theory ,Journal of Financial and Quantitative Analysis ,Management Science,Review of Finance等 。他的研究成果已發表在許多國際、全國性會議 ,受到《紐約時報》、《華爾街日報》等媒體的專訪。由於其傑出貢獻 ,韓教授獲得了衆多國際知名獎項和狗万app獎金。現任Financial Management,Journal of Economic Dynamics and Control ,Journal of Empirical Finance,International Review of Finance和Pacific-Basin Finance Journal主編和副主編 。

講座內容簡介:

Abstract:Aggregate implied volatility spread (IVS), defined as the cross-sectional average difference in the implied volatilities of at-the-money call and put equity options, is significantly and positively related to future stock market returns at daily, weekly, monthly, to semiannual horizons. This return predictive power is incremental to existing return predictors and is significant both in sample and out of sample. Furthermore, IVS can forecast macroeconomic news up to one year ahead. The return predictability concentrates around macro news announcement. Common informed trading in equity options offers an integrated explanation for the ability of IVS to predict both future stock market returns and real economic activity.