Financial data prediction with recurrent neural networks

Recurrent Neural Network is an artificial neural network model which the outputs are re-included to network input in every iteration. The biggest advantage of recurrent neural networks is that they consider the variation of each sample in the sequential data depending on the previous examples. As reccurent neural network models developed, some theoretical obstacles emerged and different models were developed as solutions to these obstacles. It can be said that Long term short term memory (LSTM) networks are one of the most popular and best designed reccurent neural network models among these models. In this study, the success of LSTM model is compared to other neural network models in evaluating financial asset prices. The LSTM model gave better classification accuracy than other compared models.