Parsimonious principle of GARCH models: a Monte‐Carlo approach
Abstract
Purpose
This paper is intended to test the robustness of the fitness of nested GARCH models.
Design/methodology/approach
Both Monte‐Carlo simulation data and real‐world data are used in the paper. Likelihood‐family tests are used to test in‐sample fitness, while mean‐squared prediction error is employed for out‐sample prediction tests.
Findings
The paper finds that, generally, the parsimonious principle is found to work well for both criteria. However, it is found that conflict exists between the two criteria: in‐sample likelihood‐family tests pay more attention to conditional distributions or are more sensitive to fat tail effects; while the out‐sample criteria focus more on the accuracy of parameter estimation.
Originality/value
The paper shows that complexity does not necessarily mean good fitness; sometimes, the simpler model can fit better, especially for real‐world data.
Keywords
Citation
Wu, J. (2006), "Parsimonious principle of GARCH models: a Monte‐Carlo approach", Journal of Risk Finance, Vol. 7 No. 5, pp. 544-558. https://doi.org/10.1108/15265940610712687
Publisher
:Emerald Group Publishing Limited
Copyright © 2006, Emerald Group Publishing Limited