Munich Personal RePEc Archive

Forecasting transaction counts with integer-valued GARCH models

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

[thumbnail of MPRA_paper_101779.pdf]

Download (1MB) | Preview


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.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.