Rolling Neural Networks

The main idea behind Rolling Neural Network is to train the model by followig the temporal structure of the data. By example we start to train over 1 year (from 01/01/2000 to 31/12/2000), predict 3 months ahead (from 01/01/2001 to 31/03/2001), and move 3 months ahead to retrain the model (from 01/04/2000 to 31/03/2001) and predict again 3 months ahead (from 01/04/2001 to 30/06/2001), and so on until present.

Rolling neural networks with Keras

fynance.neural_networks.RollNeuralNet([…])	Object to train/test a neural network along time axis.
fynance.neural_networks.RollMultiNeuralNet([…])	Rolling Multi Neural Networks object allow you to train several neural networks along training periods (from t - n to t) and predict along testing periods (from t to t + s) and roll along this time axis.
fynance.neural_networks.RollAggrMultiNeuralNet(*args)	Rolling Aggregated Multi Neural Networks object allow you to train several neural networks along training periods (from t - n to t), predict along testing periods (from t to t + s) and aggregate prediction following a specified rule and roll along this time axis.
fynance.neural_networks.RollMultiRollNeuralNet([…])	Rolling Multi Rolling Neural Networks object allow you to train several rolling neural networks along training periods (from t - n to t) and predict along testing periods (from t to t + s) and roll along this time axis.