Investigating Dynamic Correlation in the International Implied Volatility Indexes

• Main Authors: Panida Fanpaeng, Woraphon Yamaka, Roengchai Tansuchat
• Format: Book Series
• Published: 2018
• Subjects: Computer Science; Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85043998564&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/58548
• Institution: Chiang Mai University

© 2018, Springer International Publishing AG, part of Springer Nature. This paper investigates dynamic interaction among international volatility indexes, consisting of VIX, VSTOXX, VDAX, VFTSE, VNVIXN, VHSI and VKOSPI. This paper also extends the multivariate normal distribution and multivariate student-t distribution based dynamic conditional correlation (DCC) model to a multivariate skew distribution. We then apply this extended model to estimate the dynamic volatility and correlation in international volatility indexes. The empirical results of model comparison reveal the multivariate skewed student-t distribution based CGARCH-DCC model to perform the best in our real data analysis. This indicates that the time-varying conditional correlation coefficients as well as volatility are skewed and fat tailed or leptokurtic in characteristic.