This dataset and accompanying Python code support the empirical study titled "From Biofuel Illusions to Systemic Risk Pricing: Reimagining Carbon Markets for Real Climate Mitigation." The project examines how investor sensitivity to carbon pricing risk shifts under different market regimes—particularly transitions between low- and high-volatility periods. It uses a Markov Regime-Switching (MRS) model to identify nonlinear dynamics and volatility-dependent factor exposures relevant to climate finance. The analysis is based on monthly equity returns for major European energy and industrial firms (EDF, Engie, TotalEnergies, and ArcelorMittal), simulated market index returns for the CAC 40, and ICE EUA (European Union Allowance) carbon futures prices. 🔁 Replication Instructions Readers can fully replicate the study using the files provided here and Google Colab. Follow these steps: Download all files from this Zenodo repository. Open Google Colab at https://colab.research.google.com/ Upload the dataset and Python script (carbon.py) to the Colab session. Run the script using either of the following commands: !python mrs.py (to run as a standard script) or %run mrs.py (to run within an interactive cell) This script will load the datasets, clean and align the data, estimate the MRS model, and generate output tables and regime shift visualizations. Output includes: Firm-specific regression estimates across regimes Regime transition probabilities Probability plots for high- and low-volatility periods Included Files ✅ Cleaned monthly equity return data for each firm (CSV) ✅ Simulated CAC 40 market returns (CSV) ✅ Monthly carbon futures prices (ICE EUA) (CSV) ✅ carbon.py – Full Python script for replication License: Creative Commons Attribution 4.0 International (CC BY 4.0)