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Integer-valued moving average modelling of the number of transactions in stocks

  • Kurt Brannas
  • A. M. M. Shahiduzzaman Quoreshi

The Integer-valued Moving Average Model (INMA) is advanced to model the number of transactions in intra-day data of stocks. The conditional mean and variance properties are discussed and model extensions to include explanatory variables are offered. Least squares and generalized method of moment estimators are presented. In a small Monte Carlo study a feasible least squares estimator comes out as the best choice. Empirically we find support for the use of long-lag moving average models in a Swedish stock series. There is evidence of asymmetric effects of news about prices on the number of transactions.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/09603107.2010.498343
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Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 20 (2010)
Issue (Month): 18 ()
Pages: 1429-1440

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Handle: RePEc:taf:apfiec:v:20:y:2010:i:18:p:1429-1440
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  1. HEINEN, Andréas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," CORE Discussion Papers 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Brannas, Kurt & Hellstrom, Jorgen & Nordstrom, Jonas, 2002. "A new approach to modelling and forecasting monthly guest nights in hotels," International Journal of Forecasting, Elsevier, vol. 18(1), pages 19-30.
  3. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," CORE Discussion Papers 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. Kurt Brannas & Ola Simonsen, 2007. "Discretized time and conditional duration modelling for stock transaction data," Applied Financial Economics, Taylor & Francis Journals, vol. 17(8), pages 647-658.
  5. Lobato, Ignacio & Nankervis, John C & Savin, N E, 2001. "Testing for Autocorrelation Using a Modified Box-Pierce Q Test," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 187-205, February.
  6. 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.
  7. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  8. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
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