The Multivariate GARCH Model

1.1 Research Background

Volatility can be defined in several terms. Statistically, it refers to a level of uncertainty or variation of financial assets varying over time, which measured by standard deviation or variance (Baybogan, 2013). It is commonly applied in order to evaluate the risk of financial assets. Generally, assets with high volatility, the prices of these assets could dramatically fluctuate in a wider range over a short period of time. In the other word, it can be said that a higher volatility implies a higher risk of assets. However, there are a large number of papers investigate factors that could affect stock volatility. They have demonstrated that economic factors such as financial crisis, recession and inflation play a

There are a large number of academic papers emphasizing on volatility in stock markets. It has been found that most papers are based on analysis of a single asset by using univariate GARCH models and the multivariate GARCH models have been employed to investigate as bivariate or tri-variate. However, the multivariate GARCH models also have been employed in many fields of studies. The multivariate GARCH models are considered to be an appropriate and effective approach which has an ability to examine the financial asset return volatility. Another interesting application of multivariate GARCH models is to investigate volatility spillovers or volatility transmission from one market to other markets. Although there is a ton of research that have examined linkages between stock markets, a few papers applied a large number of time series to their multivariate GARCH models due to the common restrictions which might lead to difficulties of modelling and

Firstly, this study attempts to investigate the co-movements of equity market volatility in the selected counties, including the 5 Asian stock markets (Japan, Hong Kong, Singapore, South Korea and India) and one international market (U.S.). Secondly, the existence of volatility spillover effects among the selected stock markets is evidence that this paper aims to examine. As the equity markets have become more integrated and there is an increase of global financial flows, finding the volatility transmission among stock markets and their relationships would provide some useful information to investors and financial regulators. Thus, this paper seeks to find answers for these 4 following questions.

1. How did the relationship between the selected Asian stock markets and the U.S. market?

2. How multivariate GARCH models can measure volatility transmitting or contagion effects across the selected stock markets?

3. Did the price shocks and volatility in one stock market transmit to another market?

4. Did the return of a single Chinese stock market move together with other stock markets?

1.3 Summarize of dissertation structure

This paper consists of six chapters which are organized according to the following