Stock Price Prediction using LSTM

Downloads adjusted daily returns of a configurable date range and set of stocks from Yahoo Finance, concatenates them all into a long sequence, and trains an LSTM to predict future returns based on the sequence of past returns.

Specifics

• Implemented in TensorFlow, adapted from Google's PTB RNN prediction example
• Returns are normalized using standard deviation (lookback configurable). Positive drift should be negligible.
• Train / validation / test sets are organized in chronological order.

Dependencies

• TensorFlow
• pandas_datareader
• numpy

Does it work?

Not really, current results aren't much better than chance. The data might be too noisy for this method, or there might be something wrong in the code or model.