AI-Infused Algorithmic Trading: Genetic Algorithms and Machine Learning in High-Frequency 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...

Machine Learning for Market Microstructure and High Frequency Trading

In this chapter, we overview the uses of machine learning for high frequency trading and market microstructure data and problems. Machine learning is a vibrant subfield of computer science that draws on models and methods from statistics, algorithms, computational complexity, artificial intelligence, control theory, and a variety of other disciplines. Its primary focus is on computationally and...

Crashes and high frequency trading: an evaluation of risks posed by high-speed algorithmic trading

Automated Bitcoin Trading via Machine Learning Algorithms

In this project, we attempt to apply machine-learning algorithms to predict Bitcoin price. For the first phase of our investigation, we aimed to understand and better identify daily trends in the Bitcoin market while gaining insight into optimal features surrounding Bitcoin price. Our data set consists of over 25 features relating to the Bitcoin price and payment network over the course of five...

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...