@inproceedings{0b641de0fa084fb69f620324f3ad2ae5,
title = "A hidden markov model with abnormal states for detecting stock price manipulation",
abstract = "Price manipulation refers to the act of using illegal trading behaviour to manually change an equity price with the aim of making profits. With increasing volumes of trading, price manipulation can be extremely damaging to the proper functioning and integrity of capital markets. Effective approaches for analysing and real-time detection of price manipulation are yet to be developed. This paper proposes a novel approach, called Hidden Markov Model with Abnormal States (HMMAS), which models and detects price manipulation activities. Together with the wavelet decomposition for features extraction and Gaussian Mixture Model for Probability Density Function (PDF) construction, the HMMAS model detects price manipulation and identifies the type of the detected manipulation. Evaluation experiments of the model were conducted on six stock tick data from NASDAQ and London Stock Exchange (LSE). The results showed that the proposed HMMAS model can effectively detect price manipulation patterns.",
keywords = "Anomaly detection, Capital market price manipulation, Hidden markov model",
author = "Yi Cao and Yuhua Li and Sonya Coleman and Ammar Belatreche and McGinnity, \{T. M.\}",
year = "2013",
doi = "10.1109/SMC.2013.514",
language = "English",
isbn = "9780769551548",
series = "Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013",
pages = "3014--3019",
booktitle = "Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013",
note = "2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 ; Conference date: 13-10-2013 Through 16-10-2013",
}