Abstract The stock market is the main channel of financial integration for emerging economies like India. Globalization, deregulation of the market, capital account convertibility, and information and technology are the key factors contributing to the integration of the world markets. However, linkages of the financial markets are associated with risk and volatility. The ripple effects of volatility in one market can be seen in the stock markets of other countries. The ability of the country to absorb external shock depends upon the financial integration of the economy. The purpose of the paper is to analyze the degree of financial integration by estimating the volatility interdependence of stock indices of countries like India, China, USA, Germany, Japan, and UK. Time-varying correlation and volatilities among the stock market are studied using Dynamic Conditional Covariance (DCC)- Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) model and Baba , Engle, Kraft, Kroner BEKK model while the flow of information is determined through Granger Causality test. The study analyzes daily returns of SENSEX, Shanghai Stock Exchange, Dow Jones, NIKKEI, DAX and Financial Times Stock Exchange (FTSE) from 2008-2020. The study documents that the unconditional volatility is maximum in China, followed by Japan, Germany, India, USA, and UK. The financial integration of the Indian market is highest with China, followed by the USA. The policymakers can use the research findings in developing the lead-lag relation of the Indian stock market with the rest of the world. It will enable the investor to diversify their international portfolio by investing in the markets which are not correlated.