IS-Project

Stock returns prediction using RNN and LSTM neural networks

The objective of this project is to develop a prediction model using Recurrent Neural Networks (RNN). Specifically, we will explore two different approaches: Classical RNN and RNN with LSTM units. The model will be trained on historical stock price data with the aim of predicting future price movements. The task is to predict the future trend of the stock price, capturing upward and downward trends rather than exact prices, as future variations are independent of the past according to Brownian Motion.