Wong, Shiu Fung, Tong, Howell, Siu, Tak Kuen and Lu, Zudi (2017) A new multivariate nonlinear time series model for portfolio risk measurement: the threshold copula-based TAR approach. Journal of Time Series Analysis, 38 (2). pp. 243-265. ISSN 0143-9782
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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 lev
| Item Type: | Article |
|---|---|
| Official URL: | http://onlinelibrary.wiley.com/journal/10.1111/(IS... |
| Additional Information: | © 2016 John Wiley & Sons Ltd |
| Divisions: | Statistics |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management H Social Sciences > HG Finance |
| JEL classification: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C10 - General C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation G - Financial Economics > G3 - Corporate Finance and Governance > G32 - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure |
| Date Deposited: | 23 May 2017 15:06 |
| Last Modified: | 12 Dec 2024 01:29 |
| URI: | http://eprints.lse.ac.uk/id/eprint/78515 |
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