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Dhruv Sharma

Dhruv Sharma

Executive Director, MSCI Wealth Product

Dhruv Sharma leads development and application of risk models and scenario analysis for multi-asset portfolios, addressing key investment challenges for wealth management clients at MSCI. Previously, he was lead researcher and modeler for Fabric. Dhruv holds a doctorate in statistical physics and macroeconomics from Ecole Normale Supérieure, Paris, and a master’s degree in theoretical physics and a bachelor’s degree in engineering from Ecole Polytechnique, Paris.

Research and Insights

Articles by Dhruv Sharma

    Redefining Portfolio Alignment for Wealth Managers

    Research Report | Oct 30, 2024 | Dhruv Sharma, Joseph Wickremasinghe, Raina Oberoi

    The MSCI Similarity Score represents a significant evolution in wealth-management practice, aiding firms in balancing individual client needs with scalable processes and shifting perspective from a holdings-based analysis to behavioral similarity. 

    Fabric’s Approach to Scenarios

    Research Report | Dec 15, 2023 | Rick Bookstaber, Dhruv Sharma

    Scenarios are a way of positing the material risks that arise from the combination of events and market vulnerability. The core of understanding risk, the task of building scenarios, is not mechanical and is not trivial. It is alive as a narrative. 

    The Problem of Rebalancing Using Optimization Techniques

    Research Report | Oct 17, 2022 | Rick Bookstaber, Dhruv Sharma

    Mean-variance optimization is difficult to customize for a heterogeneous set of clients.  Modern technology can help advisers move from machine-driven optimization to guided rebalancing that respects market realities and client objectives.

    Managing Material Risk

    Research Report | Jul 1, 2022 | Rick Bookstaber, Dhruv Sharma

    Risk management for individuals and other asset owners differs from that of financial institutions. It’s time for a fresh mindset and new tools for these market participants. The authors propose measuring material risk through agent-based models.