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Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades

Author

Listed:
  • Gurgul Henryk

    (Department of Applications of Mathematics in Economics, Faculty of Management, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

  • Machno Artur

    (Department of Applications of Mathematics in Economics, Faculty of Management, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

Abstract

The main goal of this paper is to present the method for describing and predicting trade intensity on the Warsaw Stock Exchange. The approach is based on generalized linear models, the variable selection is performed using shrinkage methods such as the Lasso or Ridge regression. The variable under investigation is the number of trades of a particular stock 5-minute interval.

Suggested Citation

  • Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, vol. 18(1), pages 91-114, March.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:1:p:91-114:n:6
    DOI: 10.21307/stattrans-2016-059
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    References listed on IDEAS

    as
    1. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    2. Dufour, Alfonso & Engle, Robert F, 1999. "Time and the Price Impact of a Trade," University of California at San Diego, Economics Working Paper Series qt62c0h04j, Department of Economics, UC San Diego.
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    5. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
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    7. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," LIDAM Discussion Papers CORE 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Fernandes, Marcelo & Grammig, Joachim, 2005. "Nonparametric specification tests for conditional duration models," Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July.
    9. Álvaro Cartea & Thilo Meyer-Brandis, 2010. "How Duration Between Trades of Underlying Securities Affects Option Prices," Review of Finance, European Finance Association, vol. 14(4), pages 749-785.
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    More about this item

    Keywords

    high frequency data; daily trade pattern; Warsaw Stock Exchange; market microstructure; C53; G17;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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