Foreign exchange currency rate prediction using a GRU-LSTM hybrid network

The foreign exchange (FOREX) market is one of the biggest financial markets in the world. More than 5.1 trillion dollars are traded each day in the FOREX market by banks, retail traders, corporations, and individuals. Due to complex, volatile, and high fluctuation, it is quite difficult to guess the price ahead of the actual time. Traders and investors continuously look for new methods to outperform the market and to earn a higher profit. Therefore, researchers around the world are continuously coming up with new forecasting models to successfully predict the nature of this unsettled market. This paper presents a new model that combines two powerful neural networks used for time series prediction: Gated Recurrent Unit (GRU) and Long Short Term…