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Original Article | Volume 2 Issue 2 (ACR, 2025) | Pages 459 - 478
Optimizing Returns and Mitigating Risks: AI-Driven Dynamic Portfolio Rebalancing in India
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1
Research Scholar, MAKAUT, West Bengal, Assistant Professor, Department of PGDM-Business Analytics, Globsyn Business School, Kolkata.
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Principal at Post Graduate Institute of Hospital Administration, Peerless Hospital Campus, Kolkata
3
Director, Smart City and AI, Techno India University, Kolkata, West Bengal. India,
4
Associate Professor, Department of Management, Brainware University, Barasat, West Bengal, India,
5
Assistant Professor, Department of PGDM-Information Systems, Globsyn Business School, Amtala, Kolkata, West Bengal, India,
6
Assistant Professor, Institute of Engineering & Management Kolkata (University of Engineering and Management-Kolkata), India,
Under a Creative Commons license
Open Access
Abstract

AI is the one contributing factor that has turned everything topsy-turvy for property or portfolio management for emerging markets like India. Portfolio rebalancing has been done using AI for enhanced returns on investment, as well as risk mitigation, thus identifying the core financial management objective among others for dynamic portfolio rebalancing in the volatile market setting of India. AI-enabled advanced machine learning models, predictive analytics, and real-time data processing can thus lead to effective and timely portfolio adjustment by accurately identifying market shifts and risk factors. The paper identifies sectoral trends, regulatory considerations, and unique challenges towards the application of AI in the Indian context. AI-enabled portfolio rebalancing strategies that have been presented provide significantly enhanced risk-adjusted returns vis-a-vis more traditional approaches, thereby boosting investor confidence and trust. This chapter will provide useful insights for both institutional and individual investors about the all-important role of AI toward building resilient, secure and efficient investment strategies in a rapidly changing financial infrastructure.

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