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Nonlinear hedging climate policy uncertainty: A dynamic mixed copula approach

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  • Li, Jie
  • Han, Yingwei

Abstract

This paper examines the hedging performance of various green assets against climate policy uncertainty (CPU) under a dynamic and nonlinear framework. We propose a novel dynamic mixed copula model that captures time-varying nonlinear and asymmetric tail dependencies, with both copula weights and dependence parameters allowed to vary over time, to examine the hedging effectiveness of green assets. We find that the dependence between green assets and the conventional asset exhibits distinct levels and patterns during high CPU periods and low CPU periods. Among 12 green assets, world ESG- and low carbon-related equity assets are proven most effective hedging tools against the CPU shock with various risk metrics. Although the hedging performance of green bond assets are weaker than those of equity assets, the hedged portfolio with these bond assets can also generate economic values. This paper highlights the role of green assets in climate risk management.

Suggested Citation

  • Li, Jie & Han, Yingwei, 2025. "Nonlinear hedging climate policy uncertainty: A dynamic mixed copula approach," Economic Modelling, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:ecmode:v:151:y:2025:i:c:s0264999325001774
    DOI: 10.1016/j.econmod.2025.107182
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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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