# Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

arXiv: https://arxiv.org/abs/2609.01765 · HTML: https://mlsanity.com/paper/2609.01765/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 13 references that are in the map.
- First posted on arXiv 1 Sep 2026.

## Builds on (most cited first, 4 of 4)

- [Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting](https://mlsanity.com/paper/1912.09363/) (2019)
- [Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods](https://mlsanity.com/paper/1911.02508/) (2019)
- [A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME](https://mlsanity.com/paper/2305.02012/) (2023)
- [A Hybrid Deep Learning based Carbon Price Forecasting Framework with Structural Breakpoints Detection and Signal Denoising](https://mlsanity.com/paper/2511.04988/) (2025)

## Abstract (arXiv)

Carbon markets put a price on emissions, yet that price remains hard to forecast. Work in this area clusters on the EU and Chinese schemes, compresses regulatory text into a sentiment score, and reports accuracy without calibration or explanation stability. We distil ten recurring gaps into an impact-feasibility matrix and propose EPA-CarbonNet, a six-layer architecture that fuses market series with policy text by cross-attention and calibrated intervals alongside policy-attributed explanations. We then build and test it on eleven years of daily S and P carbon index data. The findings are largely negative, and reported as measured: a random walk beats the model on five-day RMSE (0.0365 against 0.0475), SHAP rankings agree at rho = 0.54 across resampled backgrounds, and policy attention never coincides with documented regulatory events. Directional accuracy, at 58.6 percent, leads every baseline. Code, data documentation and all result artifacts are available at https://github.com/Kimalice/Toward-Explainable-and-Policy-Aware-AI-for-Carbon-Credit-Price-Prediction