Economics at your fingertips  

Forecasting Market Risk of Portfolios: Copula-Markov Switching Multifractal Approach

Mawuli Segnon and Mark Trede ()

No 6617, CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster

Abstract: This paper proposes a new methodology for modeling and forecasting market risks of portfolios. It is based on a combination of copula functions and Markov switching multifractal (MSM) processes. We assess the performance of the copula-MSM model by computing the value at risk of a portfolio composed of the NASDAQ composite index and the S&P 500. Using the likelihood ratio (LR) test by Christofferrsen (1998), the GMM duration-based test by Candelon et al. (2011) and the superior predictive ability (SPA) test by Hansen (2005) we evaluate the predictive ability of the copula-MSM model and compare it to other common approaches such as historical simulation, variance-covariance, Risk-Metrics, copula-GARCH and constant conditional correlation GARCH (CCCGARCH) models. We find that the copula-MSM model is more robust, provides the best fit and outperforms the other models in terms of forecasting accuracy and VaR prediction.

Keywords: Copula; Multifractal processes; GARCH; VaR; Backtesting; SPA (search for similar items in EconPapers)
JEL-codes: C02 G17 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2017-09
New Economics Papers: this item is included in nep-ecm, nep-for, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link) ... r/cqe_wp_66_2017.pdf Version of September 2017 (application/pdf)

Related works:
Journal Article: Forecasting market risk of portfolios: copula-Markov switching multifractal approach (2018) Downloads
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:

Access Statistics for this paper

More papers in CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster Am Stadtgraben 9, 48143 Münster, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Susanne Deckwitz ().

Page updated 2024-03-23
Handle: RePEc:cqe:wpaper:6617