IDEAS home Printed from https://ideas.repec.org/a/psc/journl/v1y2009i3p261-284.html
   My bibliography  Save this article

Real-Time Market Abuse Detection with a Stochastic Parameter Model

Author

Listed:
  • Radosław Cholewiński

    (Noble Bank)

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.

Suggested Citation

  • Radosław Cholewiński, 2009. "Real-Time Market Abuse Detection with a Stochastic Parameter Model," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(3), pages 261-284, November.
    • Handle: RePEc:psc:journl:v:1:y:2009:i:3:p:261-284
    as

    Download full text from publisher

    File URL: http://cejeme.org/publishedarticles/2010-45-07-634035663581250000-8097.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Rebecca Emerson & Stephen Hall & Anna Zalewska-Mitura, 1997. "Evolving Market Efficiency with an Application to Some Bulgarian Shares," Economic Change and Restructuring, Springer, vol. 30(2), pages 75-90, May.
    3. Rockinger, Michael & Urga, Giovanni, 2000. "The Evolution of Stock Markets in Transition Economies," Journal of Comparative Economics, Elsevier, vol. 28(3), pages 456-472, September.
    4. Meulbroek, Lisa K, 1992. "An Empirical Analysis of Illegal Insider Trading," Journal of Finance, American Finance Association, vol. 47(5), pages 1661-1699, December.
    5. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    6. Zalewska-Mitura, Anna & Hall, Stephen G., 1999. "Examining the first stages of market performance: a test for evolving market efficiency," Economics Letters, Elsevier, vol. 64(1), pages 1-12, July.
    7. Watson, Mark W., 1989. "Recursive solution methods for dynamic linear rational expectations models," Journal of Econometrics, Elsevier, vol. 41(1), pages 65-89, May.
    8. Hamilton, James D., 1986. "A standard error for the estimated state vector of a state-space model," Journal of Econometrics, Elsevier, vol. 33(3), pages 387-397, December.
    9. Ray Chou & Robert F. Engle & Alex Kane, 1991. "Measuring Risk Aversion From Excess Returns on a Stock Index," NBER Working Papers 3643, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdmoulah, Walid, 2010. "Testing the evolving efficiency of Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 25-34, January.
    2. Kulikova, Maria V. & Taylor, David R. & Kulikov, Gennady Yu., 2024. "Evolving efficiency of the BRICS markets," Economic Systems, Elsevier, vol. 48(1).
    3. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    4. Charfeddine, Lanouar & Khediri, Karim Ben, 2016. "Time varying market efficiency of the GCC stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 487-504.
    5. Girardin, Eric & Liu, Zhenya, 2005. "Bank credit and seasonal anomalies in China's stock markets," China Economic Review, Elsevier, vol. 16(4), pages 465-483.
    6. Victor Dragotă & Elena Ţilică, 2014. "Market efficiency of the Post Communist East European stock markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 307-337, June.
    7. Maria Kulikova & Gennady Kulikov, 2023. "Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach," Papers 2310.04125, arXiv.org.
    8. Xiao‐Ming Li, 2003. "China: Further Evidence on the Evolution of Stock Markets in Transition Economies," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(3), pages 341-358, August.
    9. Xiao-Ming Li, 2003. "Time-varying Informational Efficiency in China's A-Share and B-Share Markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 1(1), pages 33-56.
    10. Kian-Ping Lim & Muzafar Shah Habibullah & Melvin J. Hinich, 2009. "The Weak-form Efficiency of Chinese Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(2), pages 133-163, May.
    11. Gabriele Fiorentini & Enrique Sentana & Neil Shephard, 2004. "Likelihood-Based Estimation of Latent Generalized ARCH Structures," Econometrica, Econometric Society, vol. 72(5), pages 1481-1517, September.
    12. Anatolyev, Stanislav, 2008. "A 10-year retrospective on the determinants of Russian stock returns," Research in International Business and Finance, Elsevier, vol. 22(1), pages 56-67, January.
    13. Kaie Kerem & Enn Listra & Katrin Rahu, 2004. "Market Efficiency and Rational Expectations," Working Papers 112, Tallinn School of Economics and Business Administration, Tallinn University of Technology.
    14. Christian Pierdzioch & Andrea Schertler, 2007. "Sources of Predictability of European Stock Markets for High-technology Firms," The European Journal of Finance, Taylor & Francis Journals, vol. 13(1), pages 1-27.
    15. Hanousek, Jan & Kocenda, Evzen & Kutan, Ali M., 2009. "The reaction of asset prices to macroeconomic announcements in new EU markets: Evidence from intraday data," Journal of Financial Stability, Elsevier, vol. 5(2), pages 199-219, June.
    16. Karasiński Jacek & Zduńczak Patryk, 2021. "Do extreme market value ratios mean that the market is informationally inefficient? A study of the Warsaw Stock Exchange," Journal of Economics and Management, Sciendo, vol. 43(1), pages 206-224, May.
    17. Tom A. FEARNLEY, 2002. "Tests of an International Capital Asset Pricing Model with Stocks and Government Bonds and Regime Switching Prices of Risk and Intercepts," FAME Research Paper Series rp97, International Center for Financial Asset Management and Engineering.
    18. El Hedi Arouri, Mohamed & Huong Dinh, Thanh & Khuong Nguyen, Duc, 2010. "Time-varying predictability in crude-oil markets: the case of GCC countries," Energy Policy, Elsevier, vol. 38(8), pages 4371-4380, August.
    19. Alexandru Todea & Dorina Lazar, 2012. "Global Crisis and Relative Efficiency: Empirical Evidence from Central and Eastern European Stock Markets," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 045-053, June.
    20. Ece C. KARADAGLI & Nazlı C. OMAY, 2012. "Testing Weak Form Market Efficiency Of Emerging Markets: A Nonlinear Approach," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 7(3(21)/ Fa), pages 235-245.

    More about this item

    Keywords

    Market abuse detection; insider trading; real-time analysis; timevarying parameters; uni- and bivariate GARCH processes;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G19 - Financial Economics - - General Financial Markets - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:psc:journl:v:1:y:2009:i:3:p:261-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Damian Jelito (email available below). General contact details of provider: http://cejeme.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.