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Subhajit Barman
Vice President, MSCI Research
Subhajit Barman’s research focuses on developing new strategic indexes, including indexes based on factor and ESG exposures, as well as providing solutions to clients to address their investment challenges. Before joining MSCI, he served as a quantitative strategist in portfolio management at ING Investment Management, where he helped develop factor-based model portfolios specific to each fund. Subhajit holds a postgraduate degree from the Indian Institute of Management Ahmedabad, as well as a bachelor’s degree in physics from the University of Mumbai.
Research and Insights
Articles by Subhajit Barman
Navigating the Sustainability Shift: A Challenge for Fixed-Income Investors
Research Report | Jun 12, 2024 | Jarrad Linzie, Subhajit BarmanBond investors are grappling with the challenge of balancing fiduciary responsibilities with their commitment to sustainability. Could following a decarbonization glidepath, or reinvesting cash flows to direct bond portfolios toward a climate target, help?
Quality Time: Understanding Factor Investing
Research Report | Jun 28, 2023 | Ashish Lodh, Subhajit BarmanThe past decade's market turbulence, rising inflation and fluctuating rates, has emphasized the importance of high-quality firms. This update to earlier research examines the quality factor’s role in navigating an ever-changing landscape.
How Portfolio-Weighting Schemes Affected Factor Exposures
6 mins read Blog | Oct 15, 2020 | Abhishek Gupta, Ashish Lodh, Subhajit BarmanSingle-factor portfolios seek high exposure to a target factor and limited exposure to non-target ones. We assess the impact that common portfolio weighting schemes have on these exposures, as well as on portfolio efficiency, concentration and investability.
How to Describe a Factor
5 mins read Blog | Sep 10, 2020 | Abhishek Gupta, Ashish Lodh, Subhajit BarmanHow to define a factor? It’s a challenge for asset owners and wealth managers in evaluating how well factor products meet investment objectives. We found an improved and more robust measure can be formed by combining multiple descriptors.