Detecting price manipulation in the financial market

Yi Cao*, Yuhua Li, Sonya Coleman, Ammar Belatreche, T. M. McGinnity

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Market abuse has attracted much attention from financial regulators around the world but it is difficult to fully prevent. One of the reasons is the lack of thoroughly studies of the market abuse strategies and the corresponding effective market abuse approaches. In this paper, the strategies of reported price manipulation cases are analysed as well as the related empirical studies. A transformation is then defined to convert the time-varying financial trading data into pseudo-stationary time series, where machine learning algorithms can be easily applied to the detection of the price manipulation. The evaluation experiments conducted on four stocks from NASDAQ show a promising improved performance for effectively detecting such manipulation cases.

Original languageEnglish
Title of host publication2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings
EditorsRui Jorge Almeida, Dietmar Maringer, Vasile Palade, Antoaneta Serguieva
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-84
Number of pages8
ISBN (Electronic)9781479923809
DOIs
Publication statusPublished - 14 Oct 2014
Event2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014 - London, United Kingdom
Duration: 27 Mar 201428 Mar 2014

Publication series

NameIEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)
ISSN (Print)2380-8454

Conference

Conference2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014
CountryUnited Kingdom
CityLondon
Period27/03/1428/03/14

Fingerprint Dive into the research topics of 'Detecting price manipulation in the financial market'. Together they form a unique fingerprint.

Cite this