We aim to develop univariate and multivariate stochastic models for high-frequency data of the Indian stock market. These models will be used in development of risk management and regulatory strategies.
The main problems we are considering are:
- To establish generalizations of concepts like Value at Risk to many dimensions as well as for heavy-tailed distributions.
- To find corresponding optimal hedging strategies.
- To develop regulatory strategies to mitigate the `flash crashes’ that have been observed in recent years as a consequence of high-frequency trading.
The analysis will be based on tick-by-tick data purchased from the National Stock Exchange, Mumbai.
Principal Investigator: Charu Sharma
Co-Investigators: Amber Habib, Sunil Bowry
Funding Agency: National Board for Higher Mathematics