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Panel Intensity Models with Latent Factors: An Application to the Trading Dynamics on the Foreign Exchange Market¤

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Author Info

  • Ingmar Nolte

    ()
    (University of Konstanz)

  • Valeri Voev

    ()
    (University of Konstanz)

Abstract

We develop a panel intensity model, with a time varying latent factor, which captures the influence of unobserved time effects and allows for correlation across individuals. The model is designed to analyze individual trading behavior on the basis of trading activity datasets, which are characterized by four dimensions: an irregularly-spaced time scale, trading activity types, trading instruments and investors. Our approach extends the stochastic conditional intensity model of Bauwens & Hautsch (2006) to panel duration data. We show how to estimate the model parameters by a simulated maximum likelihood technique adopting the efficient importance sampling approach of Richard & Zhang (2005). We provide an application to a trading activity dataset from an internet trading platform in the foreign exchange market and we find support for the presence of behavioral biases and discuss implications for portfolio theory.

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Bibliographic Info

Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 07-02.

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Length: 30 pages
Date of creation: 28 Feb 2007
Date of revision:
Handle: RePEc:knz:cofedp:0702

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Related research

Keywords: Trading Activity Datasets; Panel Intensity Models; Latent Factors; Efficient Importance Sampling; Behavioral Finance;

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  1. Ravi Dhar & Ning Zhu, 2002. "Up Close and Personal: An Individual Level Analysis of the Disposition Effect," Yale School of Management Working Papers ysm269, Yale School of Management, revised 01 Sep 2009.
  2. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
  3. Shefrin, Hersh & Statman, Meir, 1985. " The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-90, July.
  4. repec:att:wimass:9520 is not listed on IDEAS
  5. BAUWENS, Luc & HAUTSCH, Nikolaus, . "Stochastic conditional intensity processes," CORE Discussion Papers RP -1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, 08.
  7. Sandra Lechner & Ingmar Nolte, 2009. "Customer Trading in the Foreign Exchange Market: Empirical Evidence from an Internet Trading Platform," Working Papers wp09-01, Warwick Business School, Finance Group.
  8. Shapira, Zur & Venezia, Itzhak, 2001. "Patterns of behavior of professionally managed and independent investors," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1573-1587, August.
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