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“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”

Author

Listed:
  • Jorge Pérez-Rodríguez

    (Department of Quantitative Methods. University of Las Palmas de Gran Canaria, Spain.)

  • Emilio Gómez-Déniza

    (Department of Quantitative Methods. TiDES Institute. University of Las Palmas de Gran Canaria, Spain.)

  • Simón Sosvilla-Rivero

    (Complutense Institute for Economic Analysis, Universidad Complutense de Madrid.)

Abstract

In this paper, we attempt to assess the potential importance of different types of traders (i.e., those with public and private information) in financial markets using a specification of the standardized duration. This approach allows us to test unobserved heterogeneity in a nonlinear version based on a self-exciting threshold autoregressive conditional duration model. We illustrate the relevance of this procedure for identifying the presence of private information in the final days of trading of Banco Popular, the first bank rescued by the European Single Resolution Board.

Suggested Citation

  • Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    • Handle: RePEc:ira:wpaper:201907
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    as
    1. Giovanni Luca & Giampiero Gallo, 2009. "Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 102-120.
    2. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
    3. Albuquerque, Rui & H. Bauer, Gregory & Schneider, Martin, 2009. "Global private information in international equity markets," Journal of Financial Economics, Elsevier, vol. 94(1), pages 18-46, October.
    4. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    5. Lee, Charles M C & Mucklow, Belinda & Ready, Mark J, 1993. "Spreads, Depths, and the Impact of Earnings Information: An Intraday Analysis," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 345-374.
    6. Radner, Roy, 1979. "Rational Expectations Equilibrium: Generic Existence and the Information Revealed by Prices," Econometrica, Econometric Society, vol. 47(3), pages 655-678, May.
    7. Ghysels, Eric & Gourieroux, Christian & Jasiak, Joann, 2004. "Stochastic volatility duration models," Journal of Econometrics, Elsevier, vol. 119(2), pages 413-433, April.
    8. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    9. Ruey S. Tsay, 2009. "Autoregressive Conditional Duration Models," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 21, pages 1004-1024, Palgrave Macmillan.
    10. Easley, David & O'Hara, Maureen & Saar, Gideon, 2001. "How Stock Splits Affect Trading: A Microstructure Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(1), pages 25-51, March.
    11. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    12. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    13. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    14. Martin D. D. Evans & Richard K. Lyons, 2017. "How is Macro News Transmitted to Exchange Rates?," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 14, pages 547-596, World Scientific Publishing Co. Pte. Ltd..
    15. repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
    16. Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-872, July.
    17. T. Clifton Green, 2004. "Economic News and the Impact of Trading on Bond Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1201-1234, June.
    18. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
    19. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.
    20. BAUWENS, Luc & VEREDAS, David, 1999. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," LIDAM Discussion Papers CORE 1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. Easley, David & O'Hara, Maureen, 1992. "Adverse Selection and Large Trade Volume: The Implications for Market Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 27(2), pages 185-208, June.
    22. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    23. Sanford J. Grossman, 1981. "An Introduction to the Theory of Rational Expectations Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(4), pages 541-559.
    24. Kiefer, Nicholas M, 1984. "A Simple Test for Heterogeneity in Exponential Models of Duration," Journal of Labor Economics, University of Chicago Press, vol. 2(4), pages 539-549, October.
    25. Ghysels, Eric, 2000. "Some Econometric Recipes for High-Frequency Data Cooking," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 154-163, April.
    26. Michael W. Brandt & Kenneth A. Kavajecz, 2004. "Price Discovery in the U.S. Treasury Market: The Impact of Orderflow and Liquidity on the Yield Curve," Journal of Finance, American Finance Association, vol. 59(6), pages 2623-2654, December.
    27. Dev, Pritha, 2013. "Transfer of information by an informed trader," Finance Research Letters, Elsevier, vol. 10(2), pages 58-71.
    28. Dávila, Eduardo & Parlatore, Cecilia, 2023. "Volatility and informativeness," Journal of Financial Economics, Elsevier, vol. 147(3), pages 550-572.
    29. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    30. Aslan, Hadiye & Easley, David & Hvidkjaer, Soeren & O'Hara, Maureen, 2011. "The characteristics of informed trading: Implications for asset pricing," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 782-801.
    31. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    32. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    33. Laurent E. Calvet & Adlai Fisher, 2008. "Multifractal Volatility: Theory, Forecasting and Pricing," Post-Print hal-00671877, HAL.
    34. Paolo Pasquariello & Clara Vega, 2007. "Informed and Strategic Order Flow in the Bond Markets," The Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1975-2019, November.
    35. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
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    More about this item

    Keywords

    Conditional duration; threshold models; finite and infinite mixtures; private information; bank failure. JEL classification:C22; C41; D53; D82; G10; G12; G14.;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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