1.

Set the neural network (NN) topology by assigning l_x, H_o Equation (4) Equation (5).

2.

Chose the data for truth test that are just one or two of the last time series data that will not be used by training or validating processes.

3.

Train the NN with 85% of the data and check the overfitting with the remaining 15%.

4.

Stop the training if the generalization error increases.

5.

If the truth test data is not suitably forecasted, go to 1.

6.

Set H = 0.5, set θ via Equation (11).

7.

Run Monte Carlo including H described by Equation (10).

8.

Select the mean value that gives the best match of H according to the long or the short range scenario.

9.

The obtained mean series generated and its variance are the algorithm results.

10.

Given the case that the results were not credible, go to 6 and modify the noise characteristic by changing H, 0 < H < 1.