Abstract
This study develops a novel methodology to estimate the probability of informed trading around United Nations COP climate meetings. Analyzing data from a sample of 87 U.S.-listed fossil fuel firms between 2006 and 2023, we find that informed trading rises significantly during the [−9, 9] window. This activity generated abnormal returns of 17.565 %, or up to $25.064 billion in profit for informed traders over the relevant period. Our analysis shows that compared to fossil fuel stocks, the change in the probability of informed trading in industrials, healthcare, finance and utilities was relatively flat during COP meetings and the accumulated profit obtained by informed traders in these markets was at most $8.719 billion. Following Adler et al. (2025) who classify COP meetings by positive and negative climate policy shocks, we find that the change in the probability of informed trading around meetings with positive signals is 70.237 %, while it is 62.721 % for meetings with negative signals. We also find that the change in the probability of informed trading around COP21 (at which the Paris Agreement was adopted) was 3.544 times higher than the average across all other COP meetings, while the associated CAR was 2.118 times higher. Given the fossil fuel industry's substantial presence at COP meetings, our findings suggest that these events offer not only policy signals but also informational advantages to select market participants.
| Original language | English |
|---|---|
| Article number | 109065 |
| Pages (from-to) | 1-21 |
| Number of pages | 21 |
| Journal | Energy Economics |
| Volume | 153 |
| DOIs | |
| Publication status | Published - Jan 2026 |
Bibliographical note
© 2025 The Authors. Published by Elsevier B.V. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Climate finance
- Climate policy
- COP meeting
- Informed trading
- Net-zero transition: Fossil fuel firms
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