Predictive Risk Management Using Machine Learning in Financial Portfolios
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Abstract
This paper focuses on the application of machine learning techniques for risk management in financial portfolios. It explores how predictive models can forecast potential risks and optimize asset allocation strategies. The study employs historical market data and real-time analytics to develop ML models that enhance risk assessment and mitigation strategies, providing financial institutions with advanced tools for portfolio management.
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References
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