Abstract
This survey article reviews the current state of literature on how structural models of credit risk are employed to model the impact of climate risk on financial markets. We discuss how the two prominent types of climate risk, physical and transition risk, are captured by the seminal Merton model and its well-known extensions. Theoretical and practical advantages and drawbacks are worked out and an outlook on possible model improvements is provided.
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Notes
- 1.
Equation (5) is obtained by applying Itô’s formula to obtain the stock price dynamics.
- 2.
An alternative is to use the double-exponential distribution advocated by Kou and Wang [22].
- 3.
These models build on [25] and require the calculation of various functionals of Brownian motion.
- 4.
The distance-to-default is a measure based on the relation of the value process and the default boundary and widely used in variants of the Merton model, see [19] for further discussion.
- 5.
Using the EBITDA relies on the assumption that the proportionality to the firm value stays constant over time.
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Blasberg, A., Kiesel, R. (2024). Climate Risk in Structural Credit Models. In: Benth, F.E., Veraart, A.E.D. (eds) Quantitative Energy Finance. Springer, Cham. https://doi.org/10.1007/978-3-031-50597-3_7
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DOI: https://doi.org/10.1007/978-3-031-50597-3_7
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