CLIMATE RISK AND THE PREDICTABILITY OF JUMPS IN GREEN ASSETS

Tina Prodromou & Rıza Demirer

Applied Finance Letters2025https://doi.org/10.24135/afl.v13i.702article
ABDC B
Weight
0.41

Abstract

This paper shows that climate uncertainty can help predict the size and direction of intraday jumps in green assets, both in and out-of-sample. Using tick data to capture the size and intensity of intraday jumps, we find that news that relate to transition climate uncertainty including international summits and climate policy, particularly those that could be interpreted as bad news for brown industries, are the most dominant predictors of jumps in green assets compared to proxies of physical climate risks. Our findings provide a novel perspective to the role of climate uncertainty as a driver of idiosyncratic tail risk and jump innovations in green assets and imply that pricing models that incorporate jump risk as a risk factor can be improved by exploiting the predictive power of climate uncertainty over jump dynamics.

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https://doi.org/https://doi.org/10.24135/afl.v13i.702

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@article{tina2025,
  title        = {{CLIMATE RISK AND THE PREDICTABILITY OF JUMPS IN GREEN ASSETS}},
  author       = {Tina Prodromou & Rıza Demirer},
  journal      = {Applied Finance Letters},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.24135/afl.v13i.702},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.