Reports

Reinforcement learning is a particular area of machine learning concerned with decision making and how software agents take actions in a particular environment in order to maximize a particular function known as reward function . Theory and Concepts In Reinforcement...

In the last report we made a point on the use of Cross validation with time series. If you want to go in depth with the topic, you can read the following note produced by the University of Melbourne A Note on the Validity of Cross-Validation for Evaluating...

This report is the first of a series on machine learning applied to finance, in which we try to highlight the possible use of ML and DL in finance. Financial Prediction Markets allow you to buy and sell units of financial assets. If the prices of these...

In this article we show how the structure of an autoencoder network can be used to produce the output of an archetypal analysis reducing the computational effort. Archetypal Analysis as an autoencoder Archetypal Analysis (AA) is a data approximation method...

In this article we show how the structure of an autoencoder network can be used to produce the output of an archetypal analysis reducing the computational effort. PCA improvement and generalization with deep learning: Dimensionality reduction techniques...

An interesting article about an empirical application of a standard Machine Learning algorithm (PCA) to a market issue: the political risk implied in the 5y Italian Credit Default Swap. Italian CDS Towards Elections As Italian elections loom, we provide an...