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Artificial Intelligence (AI) has changed a large landscape of our daily life and this includes investment and financial management field. In this study the authors have studied the impact of AI in reshaping portfolio management strategies within the Indian financial market. This study comprehensively reviews over 30 academic sources and empirical data sourced from regulatory bodies such as SEBI, the Finance Ministry and PFRDA, as well as Portfolio Management Services (PMS) providers along with registered Asset Management Companies (AMCs). This paper finds the practical application of AI tools such as tools such as deep learning, machine learning, reinforcement learning, and algorithmic trading in enhancing portfolio management. In this paper the authors have focused on traditional portfolios and AI enhanced portfolios to contextualize structural shifts in portfolio management. This study has taken five performance metrics i.e., Sharpe Ratio, Compounded Annualized Growth Rate (CAGR), Standard Deviation, Alpha and Expense Ratio for consideration. The study concludes that AI enhances portfolio diversification, efficiency, risk-adjusted returns signaling a paradigm in investment management.

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AI-Enhanced Portfolio Diversification: A Five Metric Comparative Analysis with Traditional Approaches

  • 会议论文

  • 发表日期：

    2026年

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  • Ajay Gaikwad,
  • Jatinderkumar R. Saini,
  • Hema Gaikwad

摘要

Artificial Intelligence (AI) has changed a large landscape of our daily life and this includes investment and financial management field. In this study the authors have studied the impact of AI in reshaping portfolio management strategies within the Indian financial market. This study comprehensively reviews over 30 academic sources and empirical data sourced from regulatory bodies such as SEBI, the Finance Ministry and PFRDA, as well as Portfolio Management Services (PMS) providers along with registered Asset Management Companies (AMCs). This paper finds the practical application of AI tools such as tools such as deep learning, machine learning, reinforcement learning, and algorithmic trading in enhancing portfolio management. In this paper the authors have focused on traditional portfolios and AI enhanced portfolios to contextualize structural shifts in portfolio management. This study has taken five performance metrics i.e., Sharpe Ratio, Compounded Annualized Growth Rate (CAGR), Standard Deviation, Alpha and Expense Ratio for consideration. The study concludes that AI enhances portfolio diversification, efficiency, risk-adjusted returns signaling a paradigm in investment management.