Cross-Sectional Volatility Index Analysis In Asian Markets With No Derivatives Market.

In recent years, a growing literature has emerged that focuses on the performance of volatility indices in the derivatives market. The VIX has been very popular in the US market. Since its introduction in 1993, the VIX is a barometer of investor sentiment and market volatility. However, the VIX is mostly applied to markets that have derivative options price, and it turns out that less or no derivatives market would not be able to utilize the VIX as a benchmark of volatility. Chapters 1 and 2 provide an overview of the thesis and recent developments in volatility literature. Chapter 3 presents the construction of Cross-sectional Volatility Index (CSV) which is applied to an Asian market as an alternative to the VIX. One problem with the construction of a VIX-styled index is that it depends on the price of calls and puts. However, the CSV Index may be applied to measure the volatility when no derivatives market exists. Chapter 4 uses the CSV Index model to approach the no derivatives market in Southeast Asian countries. As to validate the CSV Index model, we use the GARCH family and Realized volatility models to explore the predictive power of CSV Index in a non-derivatives market. The results capture symmetric and asymmetric effects on the volatility and yields for better predictive performance. Chapter 5 provides a new empirical methodology for computing a Cross-mixed Volatility (CMV) index that characterizes the country risk understood here as the financial market risk measurement. It encapsulates all the sources of risk stemming from the financial markets for any given country. The Factor-DCC model has been adopted to construct the CMV Index and to build the composite aggregation of the CMV Index. The results exhibited that the commodities were the most prominent contribution of the composition index. Chapter 6 is the conclusion of the thesis.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Essex

Year dc:date.issued

2018

Author dc:creator

• Md Fadzil, Futeri Jazeilya binti

• HG Finance

Language dc:language

en