Using machine learning for medium frequency derivative portfolio trading
Trading and Market Microstructure
2015-12-22 v1 Machine Learning
Machine Learning
Abstract
We use machine learning for designing a medium frequency trading strategy for a portfolio of 5 year and 10 year US Treasury note futures. We formulate this as a classification problem where we predict the weekly direction of movement of the portfolio using features extracted from a deep belief network trained on technical indicators of the portfolio constituents. The experimentation shows that the resulting pipeline is effective in making a profitable trade.
Keywords
Cite
@article{arxiv.1512.06228,
title = {Using machine learning for medium frequency derivative portfolio trading},
author = {Abhijit Sharang and Chetan Rao},
journal= {arXiv preprint arXiv:1512.06228},
year = {2015}
}