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Multivariate Copula-GARCH Model and Its Applications in Financial Risk Analysis

Zhang Shi-ying

Open publisher page 7 citations

Abstract

Combined copula techniques with GARCH model,multivariate Copula-GARCH model is provided to avoid defects of classical risk analysis models.Not only is non-linear dependence between financial markets able to be caught,but also flexible multivariate distribution which can be use to analyze portfolio Value-at-Risk is able to receive from this model.Monte Carlo techniques of portfolio based on copula techniques are fully discussed in this paper.The empirical results getting from Shanghai stock markets indicate that Copula-GARCH model with different marginal distributions and Monte Carlo techniques given in this paper is feasible and effective.

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What this paper is about

Combined copula techniques with GARCH model,multivariate Copula-GARCH model is provided to avoid defects of classical risk analysis models.Not only is non-linear dependence between financial markets able to be caught,but also flexible multivariate distribution which can be use to analyze portfolio Value-at-Risk is able to receive from this model.Monte Carlo techniques of portfolio based on copula techniques are fully discussed in this paper.The empirical results getting from Shanghai stock markets indicate that Copula-GARCH model with different marginal distributions and Monte Carlo techniques given in this paper is feasible and effective.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Combined copula techniques with GARCH model,multivariate Copula-GARCH model is provided to avoid defects of classical risk analysis models.Not only is non-linear dependence between financial markets able to be caught,but also flexible multivariate distribution which can be use to analyze portfolio Value-at-Risk is able to receive from this model.Monte Carlo techniques of portfolio based on copula techniques are fully discussed in this paper.The empirical results getting from Shanghai stock markets indicate that Copula-GARCH model with different marginal distributions and Monte Carlo techniques given in this paper is feasible and effective.

Key concepts: Copula (linguistics), Econometrics, Autoregressive conditional heteroskedasticity, Value at risk, Multivariate statistics, Monte Carlo method, Multivariate t-distribution, Marginal distribution

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