<ul data-eligibleForWebStory="true"><li>Foreign exchange rate forecasting, like USD to BDT, is critical in global financial markets impacting trade and economic stability.</li><li>This study uses historical USD/BDT data from 2018-2023 to develop machine learning models for accurate forecasting.</li><li>A Long Short-Term Memory (LSTM) neural network achieves 99.449% accuracy, with an RMSE of 0.9858, outperforming ARIMA.</li><li>A Gradient Boosting Classifier (GBC) is also employed for directional prediction, revealing a 40.82% profitable trade rate.</li><li>Historical trends analysis shows a decline in BDT/USD rates and incorporates normalized daily returns for volatility.</li><li>Deep learning in forex forecasting offers traders and policymakers robust tools to mitigate risks in financial markets.</li><li>Future work may involve integrating sentiment analysis and real-time economic indicators for enhanced model adaptability.</li></ul>

Advancing Exchange Rate Forecasting: Leveraging Machine Learning and AI for Enhanced Accuracy in Global Financial Markets

Discover more