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An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-20
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms.
As a result, today’s markets experience intense activity in the highly dynamic environment where trading systems respond to others at a much faster pace than before.
This new breed of technology involves the implementation of high-speed trading strategies which generate significant portion of activity in the financial markets and present researchers with a wealth of information not available in traditional low-speed trading environments.
In this study, we aim at developing feasible computational intelligence methodologies, particularly genetic algorithms (GA), to shed light on high-speed trading research using price data of stocks on the microscopic level.
Our empirical results show that the proposed GA-based system is able to improve the accuracy of the prediction significantly for price movement, and we expect this GA-based methodology to advance the current state of research for high-speed trading and other relevant financial applications.
American Psychological Association (APA)
Huang, Chien-Feng& Li, Hsu-Chih. 2017. An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1141299
Modern Language Association (MLA)
Huang, Chien-Feng& Li, Hsu-Chih. An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-18.
https://search.emarefa.net/detail/BIM-1141299
American Medical Association (AMA)
Huang, Chien-Feng& Li, Hsu-Chih. An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1141299
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141299