 Real-Time Market Abuse Detection with a Stochastic Parameter ModelRadosław Cholewiński ()
Central European Journal of Economic Modelling and Econometrics, 2009, vol. 1, issue 3, 261-284 Abstract: This paper develops a new model of market abuse detection in real time. Market abuse is detected, as Minenna (2003) proposed, on the basis of prediction intervals. The model structure is based on the discrete-time, extended market model introduced by Monteiro, Zaman, Leitterstorf (2007) to analyze the market cleanliness. Parameters of the expected return equation are assumed, however, to be time-varying and estimated under the state-space framework using the extended Kalman filter postulated by Chou, Engle, Kane (1992) to capture the GARCH effect in returns. QML estimation is performed on intraday data; its utilization is proposed as an alternative to the continuous time modeling by Minenna (2003). This framework is generalized to the bivariate case which enables the analysis of daily open/close data. The paper also extends procedures of the statistical verification of the estimated state-space model to include the uncertainty arising from time-invariant parameters. Keywords: Market abuse detection; insider trading; real-time analysis; timevarying parameters; uni- and bivariate GARCH processes (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:1:y:2009:i:3:p:261-284 Access Statistics for this article More articles in Central European Journal of Economic Modelling and Econometrics from Central European Journal of Economic Modelling and Econometrics |
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