Document Type

Article

Publication Date

2019

DOI

10.1080/17517575.2018.1493145

Publication Title

Enterprise Information Systems

Volume

13

Issue

1

Pages

132-144

Abstract

Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and empirically evaluate the methods by grouping them into three types: technical analyses, textual analyses and high-frequency trading. Then, we evaluate the advantages and disadvantages of each method and assess their future prospects.

Comments

© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Original Publication Citation

Huang, B. M., Huan, Y. X., Xu, L. D., Zheng, L. R., & Zou, Z. (2019). Automated trading systems statistical and machine learning methods and hardware implementation: A survey. Enterprise Information Systems, 13(1), 132-144. doi:10.1080/17517575.2018.1493145

Download

Share

COinS