@inproceedings{b165d06330e84ec19dbf3aa3fcb5dac7,
title = "Detecting price manipulation in the financial market",
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.",
author = "Yi Cao and Yuhua Li and Sonya Coleman and Ammar Belatreche and McGinnity, {T. M.}",
year = "2014",
month = oct,
day = "14",
doi = "10.1109/CIFEr.2014.6924057",
language = "English",
series = "IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "77--84",
editor = "Almeida, {Rui Jorge} and Dietmar Maringer and Vasile Palade and Antoaneta Serguieva",
booktitle = "2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings",
address = "United States",
note = "2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014 ; Conference date: 27-03-2014 Through 28-03-2014",
}