by Alek | Sep 26, 2018 | Deep learning

In previous posts we proposed basic procedures necessary for performing one-step-ahead and multi-step-ahead prediction of S&P500 index based on prices of its constituents. In this post we will focus on accuracy and performance increase using dimension reduction...
by Alek | Sep 20, 2018 | Deep learning

In previous blog post we proposed how custom Deep learning neural network can be built from scratch using Python. In this post, we will present some verification and testing results. Let us consider a very simple example of learning the shape of a sinusoidal...
by Alek | Sep 15, 2018 | Deep learning

Feed-Forward Networks This post illustrates steps required to build and train feed-forward neural networks from scratch in Python. Implementing the Network in Code We will consider the following \( L \)-layer network structure \[ X^{(l)}_i=...
by Alek | Sep 1, 2018 | Deep learning

This post illustrates basic procedure necessary for performing one-step-ahead prediction of S&P500 index based on prices of its constituents using feed-forward neural networks implemented in TensorFlow using Keras API. TensorFlow is open source library for...
by Alek | Aug 17, 2018 | Applied math

Let us now attempt to predict future values of S&P500 based on the current values of the constituents. The results obtained for the prediction horizont of n=10 steps ahead will be elaborated, but the same procedure cn be applied for arbitrary n . The results...