Parsimonious principle of GARCH models: a Monte‐Carlo approach

Jing Wu

Journal of Risk Finance, 2006, vol. 7, issue 5, 544-558

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: Monte Carlo simulation; Research methods; Financial data processing (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:jrfpps:15265940610712687

DOI: 10.1108/15265940610712687

Access Statistics for this article

Journal of Risk Finance is currently edited by Nawazish Mirza

More articles in Journal of Risk Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().