Dr Debashis Guha’s paper, based on research carried out in collaboration with Prof Aditya Narvekar of S P Jain School of Global Management’s Sydney campus, has been accepted for publication by the well-known journal Data Science for Finance and Economics.

This research is part of Aditya Narvekar’s doctoral thesis, which has been supervised by Dr Guha, and it studies the use of Machine Learning to forecast corporate bankruptcies.

Dr Debashis Guha’s research paper on AI-based sector rotation, written jointly with Larry Pohlman of Adaptive Investment Solutions, and students at S P Jain School of Global Management, has been accepted for publication at the prestigious Journal of Portfolio Management.

This research was carried out in 2020 and it shows that machine learning method called “Hidden Markov Model” can identify periods of stress in market sectors and this information can be used to construct profitable portfolios.

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.