Research carried out by Dr Debashis Guha, in collaboration with Dr Lawrence Pohlman of Adaptive Investment Solutions and with the assistance of students from the S P Jain School of Global Management, shows that a machine learning method called Hidden Markov Modelling can identify periods during which the aggregate equity market or some of its sectors exhibit high volatility. Since high-volatility regimes are often associated with bear markets, this methodology can be used to construct tactical portfolios that earn higher returns than the aggregate market.

These results have been submitted for publication.