Create an AI-based Model for Dynamic Risk Management in Equity Portfolios that Accounts for Extreme Market Events (e.g., Pandemics, Financial Crises)

Abstract

The integration of Artificial Intelligence (AI) into financial risk management has opened new avenues for enhancing the resilience of equity portfolios, particularly during extreme market events such as pandemics and financial crises. This paper proposes an AI-based model for dynamic risk management in equity portfolios, aiming to address the limitations of traditional static risk models by incorporating advanced machine learning techniques and real-time data analysis. The model leverages diverse data sources, including market indicators, economic indicators, and alternative data, to predict and manage risks effectively. Through a comprehensive literature review and methodological framework, this study highlights the potential of AI in transforming risk management practices and improving portfolio performance during periods of heightened market volatility.