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A Hidden Markov Model with Abnormal States for Detecting Stock Price Manipulation

Cao, Yi, Li, Yuhua, Coleman, Sonya, Belatreche, Ammar and McGinnity, Martin (2013) A Hidden Markov Model with Abnormal States for Detecting Stock Price Manipulation. In: IEEE International Conference on Systems, Man, and Cybernetics, Manchester. IEEE. 6 pp. [Conference contribution]

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DOI: 10.1109/SMC.2013.514

Abstract

Price manipulation refers to the act of using illegaltrading behaviour to manually change an equity price withthe aim of making profits. With increasing volumes of trading,price manipulation can be extremely damaging to the properfunctioning and integrity of capital markets. Effective approachesfor analysing and real-time detection of price manipulation areyet to be developed. This paper proposes a novel approach,called Hidden Markov Model with Abnormal States (HMMAS),which models and detects price manipulation activities. Togetherwith the wavelet decomposition for features extraction andGaussian Mixture Model for Probability Density Function (PDF)construction, the HMMAS model detects price manipulationand identifies the type of the detected manipulation. Evaluationexperiments of the model were conducted on six stock tick datafrom NASDAQ and London Stock Exchange (LSE). The resultsshowed that the proposed HMMAS model can effectively detectprice manipulation patterns

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:28185
Deposited By: Dr Ammar Belatreche
Deposited On:14 Feb 2014 11:16
Last Modified:14 Feb 2014 11:16

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