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Persistence in Intertrade Durations

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Author Info
Joann Jasiak () (York University, Canada)

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Abstract

This paper examines long-term dependence in times between trades on financial markets. The autocorrelation functions of several intertrade duration series show a slow, hyperbolic rate of decay typical for long memory processes. For example, a shock to times between trades of the Alcatel stock on the Paris Stock Exchange (SBF Paris Bourse) may persist in the transactions time for a long period of 1000 or 2000 ticks. With an average duration of 52 seconds between transactions this may amount to sixteen or thirty two hours in calendar time. This paper introduces a fractionally integrated autoregressive conditional duration (FIACD) model for intertrade duration series. It also examines transformed duration processes representing times between consecutive returns to states of null, positive or negative returns. This approach captures the relationship between the duration persistence and return dynamics. The times elapsed between returns to various states feature very similar autocorrelation patterns and do not possess the long memory property. The persistence in durations is also determined by the times spent within specific states of returns. The average visiting time is state dependent, features intraday variation and may be considered as an instantaneous measure of state persistence. The long memory patterns are examined in data on the Alcatel and IBM stocks traded on the SBF Paris Bourse and NYSE.

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File URL: http://dept.econ.yorku.ca/research/workingPapers/working_papers/pers_2.pdf
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File Function: Revised version, 1999
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Paper provided by York University, Department of Economics in its series Working Papers with number 1999_8.

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Length: 40 pages
Date of creation: Aug 1996
Date of revision: Mar 1999
Handle: RePEc:yca:wpaper:1999_8

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  1. Gourieroux, Christian & Jasiak, Joanna, 1999. "Nonlinear innovations and impulse responses," CEPREMAP Working Papers (Couverture Orange) 9906, CEPREMAP. [Downloadable!]
  2. Crato, Nuno & Rothman, Philip, 1994. "Fractional integration analysis of long-run behavior for US macroeconomic time series," Economics Letters, Elsevier, vol. 45(3), pages 287-291. [Downloadable!] (restricted)
  3. Engle, Robert F & Ito, Takatoshi & Lin, Wen-Ling, 1990. "Meteor Showers or Heat Waves? Heteroskedastic Intra-daily Volatility in the Foreign Exchange Market," Econometrica, Econometric Society, vol. 58(3), pages 525-42, May. [Downloadable!] (restricted)
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  4. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July. [Downloadable!] (restricted)
  5. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May. [Downloadable!] (restricted)
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  6. Robert F. Engle & Gary G.J. Lee, 1993. "A Permanent and Transitory Component Model of Stock Return Volatility," University of California at San Diego, Economics Working Paper Series 92-44r, Department of Economics, UC San Diego. [Downloadable!]
  7. Lee, Sang-Won & Hansen, Bruce E., 1994. "Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 10(01), pages 29-52, March. [Downloadable!]
  8. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July. [Downloadable!] (restricted)
  9. Baillie, R.T. & Bollerslev, T., 1989. "Intra Day And Inter Market Volatility In Foreign Exchange Rates," Papers 8811, Michigan State - Econometrics and Economic Theory.
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  10. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September. [Downloadable!] (restricted)
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  1. Georges Dionne & Pierre Duchesne & Maria Pacurar, 2005. "Intraday Value at Risk (IVaR) Using Tick-by-Tick Data with Application to the Toronto Stock Exchange," Cahiers de recherche 0533, CIRPEE. [Downloadable!]
  2. Stanislav Anatolyev & Dmitry Shakin, 2006. "Trade intensity in the Russian stock market:dynamics, distribution and determinants," Working Papers w0070, Center for Economic and Financial Research (CEFIR). [Downloadable!]
    Other versions:
  3. Dmitri Koulikov, 2002. "Modeling Sequences of Long Memory Positive Weakly Stationary Random Variables," William Davidson Institute Working Papers Series 493, William Davidson Institute at the University of Michigan Stephen M. Ross Business School. [Downloadable!]
  4. 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!]
  5. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," Caepr Working Papers 2007-019, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington. [Downloadable!]
  6. Frank Gerhard & Nikolaus Hautsch, 2006. "A Dynamic Semiparametric Proportional Hazard Model," FRU Working Papers 2006/05, University of Copenhagen. Department of Economics. Finance Research Unit. [Downloadable!]
  7. 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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  8. 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!]
  9. Nikolaus Hautsch & Winfried Pohlmeier, 2001. "Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities," CoFE Discussion Paper 01-05, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  10. Nikolaus Hautsch, 2006. "Testing the Conditional Mean Function of Autoregressive Conditional Duration Models," FRU Working Papers 2006/06, University of Copenhagen. Department of Economics. Finance Research Unit. [Downloadable!]
  11. 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!]
    Other versions:
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