AI-Driven Financial Risk Prediction Using Machine Learning Techniques

The GARCH Risk Analysis project successfully demonstrates the use of the GARCH model for analyzing and forecasting financial market volatility. By studying historical financial data, the model effectively captures changes in risk levels and provides valuable insights into market behavior. The results highlight the importance of volatility forecasting in risk management, investment decision- making, and financial planning. Overall, the project shows that GARCH models are reliable tools for understanding and predicting financial market risk. This project presents an effective approach to financial risk analysis using the GARCH model. The model successfully estimates and forecasts market volatility based on historical price data, helping to identify periods of high and low risk. The analysis demonstrates the practical application of statistical and machine learning techniques in finance. Overall, the project provides a useful framework for risk assessment and supports better financial decision-making through accurate volatility forecasting.

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