Gradient Trader Part 1: The Surprising Usefulness of Autoencoders

This post is about a simple tool in deep learning toolbox: Autoencoder. It can be applied to multi-dimensional financial time series. Autoencoding is the practice of copying input to output or learning the identity function. It has an internal state called latent space which is used to represent the input. Usually, this dimension is chosen to be smaller than the input(called undercomplete).