{"slug": "toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for", "title": "Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets", "summary": "A new research framework, EPA-CarbonNet, proposed in an arXiv paper (2609.01765v1) for predicting carbon credit prices in emerging markets, was outperformed by a random walk baseline on five-day RMSE (0.0365 vs. 0.0475), though it achieved 58.6% directional accuracy. The study, which analyzed eleven years of S&P carbon index data, also found that SHAP rankings were unstable (rho = 0.54) and policy attention did not align with documented regulatory events.", "body_md": "arXiv:2609.01765v1 Announce Type: new\nAbstract: 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", "url": "https://wpnews.pro/news/toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for", "canonical_source": "https://arxiv.org/abs/2609.01765", "published_at": "2026-09-03 04:00:00+00:00", "updated_at": "2026-09-03 04:23:29.531356+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning"], "entities": ["EPA-CarbonNet", "arXiv", "S&P carbon index"], "alternates": {"html": "https://wpnews.pro/news/toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for", "markdown": "https://wpnews.pro/news/toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for.md", "text": "https://wpnews.pro/news/toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for.txt", "jsonld": "https://wpnews.pro/news/toward-explainable-and-policy-aware-ai-for-carbon-credit-price-prediction-a-for.jsonld"}}