Wednesday July 6 2016
Scuola Normale Superiore
Jawaharlal Nehru University, New Delhi, India
First, we review the techniques of decomposing aggregate correlation matrices to study co-movements in financial data. We apply the techniques to daily return time series from the Indian stock market. Secondly, we use the multi-dimensional scaling methods to visualise the dynamic evolution of the stock market. This method helps to differentiate sectors in the market in the form of clusters. The other objective is to detect periods of instability in the market. Finally, our aim is to decompose the aggregate volatility into sectoral components. Such a mapping allows us to study impact of different sectors on the market behaviour and vice versa.