Abstract
This paper explores the possible linkages between Shanghai and Bombay stock markets, accounting for complimentarity (through direct linkages) and substitutability (through indirect linkages) features between China and India to confirm real linkages in physical world. We employ a Dynamic OLS estimation proposed by Stock and Watson (1994) to estimate long run relationship between two variables. Considering the long memory feature of financial data, we apply the ARFIMA regression to our cointegrated residual derived from Dynamic OLS estimation. While differencing cointegrated residual with fractionally integrated order of d value, we estimate the long term and short dynamic relations of index returns in two stock markets, with the help of VECM equation. Furthermore, we apply a DCC-MGARCH model to analyze ARCH effect, GARCH effect, and volatility transmission between two stock markets. We use Quantile regression approach to study dependence structure and intensity at different quantiles between two markets. Dummy variables are taken to distinguish pre-crisis periods and in crisis, post-crisis periods.
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