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Feature Description
Integrate a Foreign Exchange (Forex) Rate Prediction model into the project. This feature should include various machine learning and deep learning algorithms, such as LSTM, and Random Forest, to analyze historical exchange rate data and predict future trends. The system should support data preprocessing, feature engineering, model training, validation, and deployment. Users should be able to input historical Forex data, select prediction horizons, and visualize the predicted exchange rates.
Use Case
In real-life applications, the Foreign Exchange Rate Prediction model can significantly benefit financial institutions, traders, and businesses engaged in international trade. Accurate predictions of Forex rates enable traders to make informed decisions, reducing risks and maximizing profits. For financial institutions, such predictions can aid in managing foreign currency reserves and optimizing transaction costs. Businesses involved in import/export activities can use the predictions to plan better and hedge against currency risks, ensuring more stable financial operations. Integrating this feature allows users to leverage advanced predictive analytics, enhancing decision-making and strategic planning in the volatile Forex market.
Priority
High
Record