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Asymmetric ACD models: Introducing price information in ACD models

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Luc Bauwens
Pierre Giot ()

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Abstract

This paper proposes an asymmetric autoregressive conditional duration (ACD) model, which extends the ACD model of Engle and Russell (1998). The asymmetry consists of letting the duration process depend on the state of the price process. If the price has increased, the parameters of the ACD model can differ from what they are if the price has decreased. The model is applied to the bid-ask quotes of two stocks traded on the NYSE and the evidence in favour of asymmetry is strong. Information effects (Easley and O'Hara 1992) are also empirically relevant. As the model is a transition model for the price process, it delivers `market forecasts' of where prices are heading. A trading strategy based on the model is implemented using tick-by-tick data. Copyright Springer-Verlag 2003

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File URL: http://hdl.handle.net/10.1007/s00181-003-0155-7
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Publisher Info
Article provided by Springer in its journal Empirical Economics.

Volume (Year): 28 (2003)
Issue (Month): 4 (November)
Pages: 709-731
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Handle: RePEc:spr:empeco:v:28:y:2003:i:4:p:709-731

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Related research
Keywords: Duration and transition model; high frequency data; market microstructure; forecasting;

Cited by:
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  1. BELTRAN, Helena & DURRE, Alain & GIOT, Pierre, 2005. "Volatility regimes and the provision of liquidity in order book markets," CORE Discussion Papers 2005012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
    Other versions:
  2. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Research series 200405-5, National Bank of Belgium. [Downloadable!]
  3. Christian M. Hafner, 2000. "Durations, Volume and the Prediction of Financial Returns in Transaction Time," Econometric Society World Congress 2000 Contributed Papers 0599, Econometric Society. [Downloadable!]
  4. Ahmed M. Khalid & Gulasekaran Rajaguru, 2004. "Financial Market Linkages in South Asia: Evidence Using a Multivariate GARCH Model," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 43(4), pages 585-603. [Downloadable!]
  5. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March. [Downloadable!] (restricted)
  6. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
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  7. 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. [Downloadable!]
  8. Pierre Giot & Armin Schwienbacher, 2003. "IPOs, Trade Sales and Liquidations: Modelling Venture Capital Exits Using Survival Analysis," Finance 0312006, EconWPA. [Downloadable!]
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  9. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006. [Downloadable!]
  10. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society. [Downloadable!]
  11. Winfried Pohlmeier & Roman Liesenfeld, 2003. "A Dynamic Integer Count Data Model for Financial Transaction Prices," CoFE Discussion Paper 03-03, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  12. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63. [Downloadable!]
  13. BAUWENS, Luc & VEREDAS, David, 1999. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," CORE Discussion Papers 1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
  14. Dinghai Xu & John Knight & Tony S. Wirjanto, 2008. "Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"," Working Papers 08007, University of Waterloo, Department of Economics. [Downloadable!]
  15. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society. [Downloadable!]
  16. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Working Papers 13-2007, Singapore Management University, School of Economics. [Downloadable!]
  17. Frank Gerhard & Nikolaus Hautsch, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Paper 99-19, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
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