Machine learning for algorithmic trading

Algorithmic Trading of Futures via Machine Learning

A lgorithmic trading of securities has become a staple of modern approaches to financial investment. In this project, I attempt to obtain an effective strategy for trading a collection of 27 financial futures based solely on their past trading data. All of the strategies that I consider are based on predictions of the future price and volatility of the various securities under consideration, an...

Algorithmic Trading Using Machine Learning Tech- Niques: Final Report

In this report, we present an automatic stock trading process, which relies on a hierarchy of a feature selecting method, multiple machine-learning algorithms as well as an online learning mechanism. Backward search was used in feature selection, while the local linear regression (LLR), l − 1 regularized ν-support vector machine (ν-SVM), and the multiple additive regression tree (MART), were ch...

Learning Gated Bayesian Networks for Algorithmic Trading

Abstract. Gated Bayesian networks (GBNs) are a recently introduced extension of Bayesian networks that aims to model dynamical systems consisting of several distinct phases. In this paper, we present an algorithm for semi-automatic learning of GBNs. We use the algorithm to learn GBNs that output buy and sell decisions for use in algorithmic trading systems. We show how using the learnt GBNs can...

Algorithmic Aspects of Machine Learning

Algorithmic Aspects of Machine Learning, Textbook