A New Multivariate Nonlinear Time Series Model for Portfolio Risk Measurement: The Threshold Copula‐Based TAR Approach. (15th August 2016)

• Record Type: Journal Article
• Authors: Wong, Shiu Fung; Tong, Howell; Siu, Tak Kuen; Lu, Zudi
• Other Names: Subba Rao Tata guestEditor.; Tunnicliffe Wilson Granville guestEditor.
• Is Part Of: Journal of time series analysis. Volume 38:Number 2(2017:Mar.)
• Page Start: 243
• Page End: 265
• Publication Date: 2016-08-15
• Subjects: Quantitative risk measures -- copulas -- multivariate nonlinear time series -- threshold principle; Time-series analysis -- Periodicals; 519.232
• DOI: 10.1111/jtsa.12206
• Languages: English
• ISSNs: 0143-9782

Abstract

Abstract : We propose a threshold copula‐based nonlinear time series model for evaluating quantitative risk measures for financial portfolios with a flexible structure to incorporate nonlinearities in both univariate (component) time series and their dependent structure. We incorporate different dependent structures of asset returns over different market regimes, which are manifested in their price levels. We estimate the model parameters by a two‐stage maximum likelihood method. Real financial data and appropriate statistical tests are used to illustrate the efficacy of the proposed model. Simulated results for sampling distribution of parameters estimates are given. Empirical results suggest that the proposed model leads to significant improvement of the accuracy of value‐at‐risk forecasts at the portfolio level.