This study examines the spatial dependence by employing spatial econometric technique to investigate whether economic channels and geographical distance matter for the determination of stock market returns. The empirical analysis is based on Asians stock market over a period from 1980 to 2016.We have estimated the Spatial Durbin Model (SDM) because it not only capture the spatial effects in returns but from explanatory variables as well, otherwise if we apply the OLS estimation it will produce the biased and inconsistent parameters due to ignorance of spatial dependence. In our analysis market returns are not affected by the fundamental variables, but the weighted averages of other markets returns and fundamentals as well. Results show that among the three integration measures (exchange rate volatility, bilateral trade and geographical distance), the important link is bilateral trade while the geographical distance is least in explaining the impact on stock returns. Fundamental variables that are included in the model which impact stock return, among them influential variables are exchange rate, GDP growth and interest rate. In case of exchange rate volatility (integration measure), only indirect effect is significant for the fundamental variable “changes in exchange rate”. On the other hand when bilateral trade is used as an integration measure, then the direct effect is positive for GDP growth and negative for interest rate, while its indirect effect is positive only for GDP growth. In case of geographical distance direct effect is significant in case of GDP growth and interest rate. Supervisor:- Dr. Hafsa Hina