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A Continual Learning Approach for Robust and Adaptive Financial Forecasting
Financial markets are dynamic, volatile, and constantly influenced by unpredictable factors, making accurate forecasting a significant challenge.
Traditional Machine Learning models often struggle to adapt to shifting market conditions, leading to unstable predictions.
In this white paper, we explore how Alternate Experience Replay (AER), a Continual Learning technique, can enhance AI-driven financial forecasting by reducing information loss and improving model adaptability.
Discover how this approach helps retain valuable historical insights while integrating new market data, ultimately improving prediction accuracy and stability in ever-changing financial environments.
