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Inferring information from S&P 500 and CBOE indices: The more the merrier?

2019-09-27 14:00

报告人: Jiling Cao

报告人单位: Auckland University of Technology, New Zealand

时间: 2019-09-27 14:00-15:00

地点: 北洋园校区32楼B区218

开始时间: 14:00

报告人简介: 教授

年: 2019

日月: 09.27

摘要:

The Chicago Board Options Exchange (CBOE) updated the CBOE Volatility Index

(VIX) in 2003 and further launched the CBOE Skew Index (SKEW) in 2011, in order to measure

the 30-day risk-neutral volatility and skewness of the S&P 500 Index (SPX). In this work, we

mainly compares the information extracted from the SPX and CBOE indices in terms of the

SPX option pricing performance. Based on our analysis, VIX is a very informative index

for option prices. Whether adding the SKEW or the VIX term structure can improve the

option pricing performance depends on the model we choose. Roughly speaking, the VIX term

structure is informative for some models, while, the SKEW is very noisy and does not contain

much important information for option prices.

简介:

Professor Jiling Cao is the Head of Mathematical Sciences Department, discipline

leader of Mathematical Sciences and and a doctoral student advisor in Auckland University

of Technology, New Zealand. He is a member of the American Mathematical Society, a fellow

of the New Zealand Mathematical Society, a reviewer for both of Mathematical Reviews and

Zentralblatt MATH. He has been a reviewer for many international journals. Prof Cao also

held visiting professorships and research fellowships in Japan, China, Brazil and India. He has

delivered invited addresses at many institutes and international conferences. Prof Cao's research

interests include nancial mathematics, mathematical economics and mathematical analysis.

He has authored and co-authored over 80 research papers, some of which are published in leading

journals in these areas. In his research work, Prof Cao has solved open problems posed by

McCoy and Gruenhage in analytic topology in 1975 and 2000 respectively, and open problems

posed by Herves-Beloso and Pesces in mathematical economics by applying the methods in

mathematical analysis. Currently, his research is focused on rough stochastic modeling and

derivatives pricing.


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