fynance.neural_networks.RollMultiRollNeuralNet.run¶

RollMultiRollNeuralNet.run(y, X, NN, weights=[], plot_loss=True, plot_perf=True, x_axis=None, reset_nn=True)¶

Train several rolling neural networks along pre-specified train period and predict along test period. Display loss and performance if specified.

Parameters:

Parameters:	y : np.ndarray[np.float32, ndim=2] with shape=(T, 1) Time series of target to estimate or predict. X : np.ndarray[np.float32, ndim=2] with shape=(T, N) Several time series of features. NN : keras.Model or list of keras.Model Neural networks to train and predict. plot_loss : bool, optional If true dynamic plot of loss function, default is True. plot_perf : bool, optional If true dynamic plot of strategy performance, default is True. x_axis : list or array, optional x-axis to plot (e.g. list of dates).
Returns:	rmrnn : RollMultiRollNeuralNet (object)

y : np.ndarray[np.float32, ndim=2] with shape=(T, 1): Time series of target to estimate or predict.
X : np.ndarray[np.float32, ndim=2] with shape=(T, N): Several time series of features.
NN : keras.Model or list of keras.Model: Neural networks to train and predict.
plot_loss : bool, optional: If true dynamic plot of loss function, default is True.
plot_perf : bool, optional: If true dynamic plot of strategy performance, default is True.
x_axis : list or array, optional: x-axis to plot (e.g. list of dates).

Returns: