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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: G17 C02 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-for, nep-ore and nep-rmg
Date: 2017-09
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Journal Article: Forecasting market risk of portfolios: copula-Markov switching multifractal approach (2018) Downloads
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