Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach

Herrera, Rodrigo; González, Sergio; Clements, Adam

doi:10.1016/j.najef.2018.03.010

Cited by 2 publications

(1 citation statement)

References 43 publications

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“…Therefore, an appropriate measure of extreme value dependence in the market has become a key issue. Combining the Copula function with extreme value theory as suggested by Sklar [19], some scholars, including Wang et al [20], Berger [21], Hussain and Li [22], and Herrera et al [23], have created an EVT-copula model to characterize the extreme dependence between financial markets. Jiang and Ye [24] integrate the EVT and the risk value model based on conditional variance, to measure and assess the short-term risks of the carbon spot market under the EU emission trading scheme.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling the Risk of Extreme Value Dependence in Chinese Regional Carbon Emission Markets

Qiu

Yang

et al. 2020

Sustainability

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In this study, we analyze the risk of extreme value dependence in Chinese regional carbon emission markets. After filtering the daily return data of six carbon markets in China using a generalized autoregressive conditional heteroscedasticity (GARCH) model, we obtain the standardized residual series. Next, the dependence structures in the markets are captured by the Copula function and the Extreme Value theory (EVT). We report high peaks, heavy tails and fluctuation aggregation in the logarithm return series of the markets, as well as significant dependent structures. There are significant extreme value risks in Chinese regional carbon markets, but the risks can be mitigated through appropriate portfolio diversification.

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