A Vector Integer-Valued Moving Average Modelfor High Frequency Financial Count Data
A vector integer-valued moving average (VINMA) model is introduced. The VINMA model allows for both positive and negative correlations between the counts. The conditional and unconditional first and second order moments are obtained. The CLS and FGLS estimators are discussed. The model is capable of capturing the covariance between and within intra-day time series of transaction frequency data due to macroeconomic news and news related to a specific stock. Empirically, it is found that the spillover effect from Ericsson B to AstraZeneca is larger than that from AstraZeneca to Ericsson B
|Date of creation:||11 Apr 2006|
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- Kurt Brannas & A. M. M. Shahiduzzaman Quoreshi, 2010.
"Integer-valued moving average modelling of the number of transactions in stocks,"
Applied Financial Economics,
Taylor & Francis Journals, vol. 20(18), pages 1429-1440.
- Brännäs, Kurt & Quoreshi, Shahiduzzaman, 2004. "Integer-Valued Moving Average Modelling of the Number of Transactions in Stocks," Umeå Economic Studies 637, Umeå University, Department of Economics.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Robert F. Engle, 1996.
"The Econometrics of Ultra-High Frequency Data,"
NBER Working Papers
5816, National Bureau of Economic Research, Inc.
- Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984.
"Pseudo Maximum Likelihood Methods: Applications to Poisson Models,"
Econometric Society, vol. 52(3), pages 701-20, May.
- Gourieroux Christian & Monfort Alain & Trognon A, 1982. "Pseudo maximum lilelihood methods : applications to poisson models," CEPREMAP Working Papers (Couverture Orange) 8203, CEPREMAP.
- Quoreshi, Shahiduzzaman, 2005. "Bivariate Time Series Modelling of Financial Count Data," Umeå Economic Studies 655, Umeå University, Department of Economics.
- Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
- 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.
- Quoreshi, Shahiduzzaman, 2006. "LongMemory, Count Data, Time Series Modelling for Financial Application," Umeå Economic Studies 673, Umeå University, Department of Economics.
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