/StockCNN

Attempting to use a Constitutional Neural Network to make daily high-low-close predictions from previous daily data.

Primary LanguagePython

StockCNN

Attempting to use a CNN to make daily high-low-close predictions from previous intra-day data.

This is a work in progress to scrape intra-day ticker data and use that as a continuous 1D-signal, and utilize a CNN to attempt to predict the following day's HLC.

symbols_getter.py scrapes all of the individual tickers.

historical_scraper.py scrapes the entire availble history of minute by minute data from all the the tickers from symbols_getter.py

preprocess_json.py parses out the json format from historical_scraper.py into a csv format.

make_training.py parses the csv data into a labeled training data.

CNNreg.py uses the training data to train a CNN, with the labeled previous day (390,1) array with the following day's HLC.

predictions.py uses the CNN to make predictions on the next available day in the data.