Orrie Stentoft posted an update 3 days, 11 hours ago
Engle and Patton (2001) harped on the theme that a volatility model must be able to forecast volatility, which this is the central requirement in almost all-financial applications. Their conclusion was that pronounced persistence and mean-reversion, asymmetry such that the sign of an innovation also affects volatility and the possibility of exogenous or pre-determined variables influencing volatility. Chan, Lien, and Weng (2008) studied causal relationship between Hong Kong and US financial markets, using band spectrum regression techniques to examine the dynamic properties of the interactions between capital markets. They found that before the Asian financial crisis there is a feedback relationship between the two markets which is driven by long cycles (with low frequencies), while post-911 periods, there is a one-way causality from the US market to the Hong Kong market.Li (2007) examines the linkages between the two emerging stock exchanges in mainland China and the established markets in Hong Kong and in the US by a multivariate GARCH approach. The results indicated no evidence of a direct linkage between the stock exchanges in mainland China and the US market, but found evidence of uni-directional volatility spillovers from the stock exchange in Hong Kong to those in Shanghai and Shenzhen. The implication of the weak (-)-p-Bromotetramisole Oxalate is that by investing in Chinese market overseas investors will benefit from the reduction of diversifiable risk.Several empirical regularities can be spotted from the research undertaken in this field. It can be said that the volatility of stock price is time varying and when volatility is high, the price changes in major markets tend to become highly correlated. Moreover correlation in volatility and prices appear to be causal from the United States to other countries; and lagged spillovers of price changes and price volatility are found between major markets.It is with setting, this paper proceeds to examine the direction and extend of mean spillovers and volatility spillovers across five stock markets. The rest of the paper is organized as follows: Section 3 explains the research method and describes the data used in the study, Section 4 describes the model and discusses the results, Section 5 concludes.3. Research method and data descriptionIn this study, we adopt one model GARCH-M to analyze a financial time series data to see for volatility spillover effects. This paper aims at investigating the issue of volatility spillovers across national stock markets for the period 2001 to 2011. This study is mainly based on secondary data that have been collected from the database on Indian economy maintained by Reserve Bank of India. To test for the presence of volatility spillovers a return series is required which can be sampled. The study undertaken uses the Weighted Average Stock Price Index as a measure of stock market return. Consequently the return series for each market is chosen on the basis of the market index which provides an historical daily time-series.