Abstract
Sectoral co-movements in the Indian stock market: A mesoscopic network analysis by Kiran Sharma Stock market is a fascinating example of a rapidly evolving multi-agent interacting system that generates an enormous amount of very well defined and well documented data. We reviewed several techniques to extract information from stock market data. We discussed decomposition of aggregate correlation matrices to study the co-movements in financial data, stock level partial correlations with market indices, multidimensional scaling and minimum spanning tree. We presented a series of analysis on to the daily return time series from the Indian stock market, using both macro scale and micro scale data.The analysis allowed us to construct networks based on correlation matrices of individual stocks in one hand and on the other, we discussed dynamics of market indices. Thus, both micro level and macro level dynamics can be analyzed using such tools.
We used the multi-dimensional scaling methods to visualize the sectoral structure of the stock market, and analyzed the co-movements among the sectoral stocks. Finally, we constructed a mesoscopic network based on sectoral indices. Minimum spanning tree technique seen to be extremely useful in order to separate technologically related sectors and the mapping corresponds to actual production relationship to a reasonable extent.