Statistical Learning using Market Microstructure Data

Identify different types of trading behavior and classify traders in various categories, using a high frequency dataset on the energy derivatives market. Build upon the rare events methodology recently developed by us. The methodology will be expanded to multiple asset classes and by decomposing the trader interaction matrix will be able to identify the changes in fundamental reason why traders are trading thus potentially helping regulators detect changes in market behavior.