Predicting stock prices with LSTM network

This project goal is to demonstrate how to use LSTM networks and apply in some real data.

Getting Started

In this repository, you will find the following notebook:

Moving Average: First look at the data, a SMA and EMA model
Sanity Check: A test with LSTM and the model used to make sure the model works
LSTM input and output: An explanation on how I manipulated the data to use as input/output for the model
LSTM Single Company: A LSTM model used to predict the closing price of a single company. Note that the notebooks ‘Single Company B’, ‘Single Company C’ and ‘Single Company D’ are extremely similar.
LSTM multi-companies prediction: A LSTM model used to predict the closing price of all four companies (A, B, C and D).

The code was written in Python, and uses:

A LSTM network is not able to predict the closing price behaviour by only looking at its historical data.

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
Data-Sanity		Data-Sanity
Trained		Trained
data		data
LSTM Single Company.ipynb		LSTM Single Company.ipynb
LSTM input and output.ipynb		LSTM input and output.ipynb
LSTM multi-companies prediction.ipynb		LSTM multi-companies prediction.ipynb
Moving Average.ipynb		Moving Average.ipynb
Readme.md		Readme.md
Sanity Check.ipynb		Sanity Check.ipynb
Single Company - B.ipynb		Single Company - B.ipynb
Single Company - C.ipynb		Single Company - C.ipynb
Single Company - D.ipynb		Single Company - D.ipynb