Aknouche, Abdelhakim and Almohaimeed, Bader and Dimitrakopoulos, Stefanos (2020): Forecasting transaction counts with integervalued GARCH models.

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Abstract
Using numerous transaction data on the number of stock trades, we conduct a forecasting exercise with INGARCH models, governed by various conditional distributions. The model parameters are estimated with efficient Markov Chain Monte Carlo methods, while forecast evaluation is done by calculating point and density forecasts.
Item Type:  MPRA Paper 

Original Title:  Forecasting transaction counts with integervalued GARCH models 
English Title:  Forecasting transaction counts with integervalued GARCH models 
Language:  English 
Keywords:  Count time series, INGARCH models, MCMC, Forecasting comparison 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C18  Methodological Issues: General C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics 
Item ID:  101779 
Depositing User:  Prof. Abdelhakim Aknouche 
Date Deposited:  15 Jul 2020 09:18 
Last Modified:  15 Jul 2020 09:18 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/101779 