Spatial modeling of stock market comovements

We model the complex global dependencies in international financial markets using spatial techniques. Our methodology allows us to go beyond conventional correlation analyses and volatility-spillover models confined to studying pairwise relationships, and improves the accuracy of return predictions. We find that stock market comovements are unrelated to geographical proximity, and that financial linkages, as measured by foreign direct investment (FDI) ties, are important in accounting for markets comovements. Our results suggest that the proposed measure of financial distance, coupled with spatial methodology, captures fairly accurately the dependencies in the world financial markets, providing important implications for policymaking and portfolio management.