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2013•Advanced materials researchOpen access

Estimating the Portfolio Risk with Copula-GARCH-EVT Method: Empirical Study of Carbon Market

Ting Li, Zhi Gang Zhang, Lu‐Tao Zhao

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Abstract

With the rapid growth of the carbon market, carbon price fluctuations are increasingly important for market participants. Carbon market risk directly affects the investor confidence and emission reduction results. In this paper we use Copula-GARCH-EVT model to calculate the Value-at-Risk of carbon futures via Monte Carlo method and demonstrate that GARCH-EVT model is the proper marginal distribution, it has higher accuracy than other marginal distribution models. The method of Copula is better than the traditional covariance metric method.

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What this paper is about

With the rapid growth of the carbon market, carbon price fluctuations are increasingly important for market participants. Carbon market risk directly affects the investor confidence and emission reduction results. In this paper we use Copula-GARCH-EVT model to calculate the Value-at-Risk of carbon futures via Monte Carlo method and demonstrate that GARCH-EVT model is the proper marginal distribution, it has higher accuracy than other marginal distribution models. The method of Copula is better than the traditional covariance metric method.

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Available abstract

With the rapid growth of the carbon market, carbon price fluctuations are increasingly important for market participants. Carbon market risk directly affects the investor confidence and emission reduction results. In this paper we use Copula-GARCH-EVT model to calculate the Value-at-Risk of carbon futures via Monte Carlo method and demonstrate that GARCH-EVT model is the proper marginal distribution, it has higher accuracy than other marginal distribution models. The method of Copula is better than the traditional covariance metric method.

Key concepts: Copula (linguistics), Autoregressive conditional heteroskedasticity, Econometrics, Futures contract, Value at risk, Marginal distribution, Portfolio, Carbon market

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