Forex Market Analysis Using Deep Learning Approaches

  • Authors

    • Kalluri Ram Rohith Reddy Undergraduate Student
    • Kankanala Kowsick Raja Undergraduate Student
    • P Subham Undergraduate Student
    • Puspanjali Mohapatra Assistant professor
    2024-07-04
    https://doi.org/10.14419/exx69554
  • Forex, Forex Market, Indian Rupee, Japanese Yen, British Pound, US Dollar, MSE, RMSE, MAE, LSTM, GRU

  • Abstract

    This paper compares the effectiveness of various deep learning models which includes LSTM (Long-Short Term Memory) and GRU (Gated Recurrent Unit) models. These models use three exchange currency pairs named Euro to US Dollar, British Pound to US Dollar, and Indian Rupee to Japanese Yen for the purpose of training and performance comparison. The analysis is conducted daily according to time zones. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) performance measures are used to compare different models. According to the observations, the GRU model outperformed the LSTM model in the majority of datasets.

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  • How to Cite

    Reddy, K. R. R. ., Raja, K. K. ., Subham, P. ., & Mohapatra, P. (2024). Forex Market Analysis Using Deep Learning Approaches. Journal of Advanced Computer Science & Technology (JACST), 12(2), 41-52. https://doi.org/10.14419/exx69554