This is a small project for the course "Python for Finance and Data Science" at ESILV, based on the data challenge proposed by QRT and College de France.
It is also my first real approach with Deep Learning in Python and Keras.
The challenge consists in the prediction of the next-day market movement of a stock, providing historical data on returns and volumes in the 20 previous trading days.
Dataset contains data for many different anonymized stocks, groupable according to market sector and industry.
Datasets must be downloaded from:
https://challengedata.ens.fr/challenges/23
and putted in a folder:
"_res\[DATASETS.csv]"