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Environmental CVA with K-Robust Wrong-Way Risk

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  • Takayuki Sakuma

Abstract

Although climate and nature related scenario analysis is increasingly important in finance, operational implementations remain limited for translating long horizon environmental scenarios into counterparty credit risk measures used in pricing and regulatory capital. We propose an environmental valuation adjustment framework for CVA with three components: (i) a scenario to credit translation that maps environmental scenario drivers into hazard rates; (ii) nature specific tail generators that quantify model risk in scenario generation; and (iii) a distributionally robust wrong way risk bound based on Kullback Leibler (KL) divergence. We compute climate CVAs using transition scenarios and nature CVAs using biodiversity indicators. Our results show that nature CVAs can vary materially across alternative ecosystem generators, highlighting an additional source of model uncertainty.

Suggested Citation

  • Takayuki Sakuma, 2026. "Environmental CVA with K-Robust Wrong-Way Risk," Papers 2603.23842, arXiv.org, revised Mar 2026.
    • Handle: RePEc:arx:papers:2603.23842
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    References listed on IDEAS

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    2. Paul Glasserman & Linan Yang, 2018. "Bounding Wrong†Way Risk In Cva Calculation," Mathematical Finance, Wiley Blackwell, vol. 28(1), pages 268-305, January.
    3. Yuhong Xu, 2014. "Robust valuation and risk measurement under model uncertainty," Papers 1407.8024, arXiv.org.
    4. Paul Glasserman & Xingbo Xu, 2014. "Robust risk measurement and model risk," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 29-58, January.
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