地政学的ショック、化石燃料市場、クリーンエネルギー移行：AIセンチメントとテクニカル指標を用いた原油・天然ガス・再生可能エネルギーのデータ駆動型レジーム分析（2020–2026）
Geopolitical Shocks, Fossil Fuel Markets, and the Clean Energy Transition: A Data-Driven Regime Analysis of Crude Oil, Natural Gas, and Renewable Energy Using AI Sentiment and Technical Indicators (2020–2026) (原題)
Podgórski K, Kral-Grabka D
🤖 gxceed AI 要約
日本語
2020〜2026年の時間足データを用い、RSIにADXレジームフィルターとLLMによる地政学センチメントを組み合わせたハイブリッド判断枠組みを検証。センチメントの効果はレジーム依存で、天然ガスの保ち合い局面とWTIで最も改善するが、勝率や最大ドローダウンは体系的に改善しない。再生可能電力代理のNextEraは炭化水素ショック下で高い耐性を示し、クリーンエネルギーへの資本代替を示唆する。
English
Using hourly 2020–2026 data, the study tests a hybrid framework combining RSI with an ADX regime filter and LLM-quantified geopolitical sentiment across WTI, Brent, Henry Hub gas, and NextEra as a renewables proxy. Sentiment gains are regime-dependent, largest for gas in consolidation and for WTI, without systematic win-rate or drawdown improvement. NextEra shows superior resilience, consistent with capital substitution toward clean energy during hydrocarbon shocks.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のGX実務への直接の開示規制連動は薄いが、エネルギー安全保障と化石燃料価格ショックが再生可能電力への資本配分をどう変えるかは、日本の電力・エネルギー政策およびトランジション戦略を考える上で示唆がある。
In the global GX context
Adds to global transition-finance scholarship by quantifying how geopolitical shocks reallocate capital toward clean-energy equities, relevant to energy-security and decarbonization policy debates amid ISSB/TCFD-aligned transition planning.
👥 読者別の含意
🔬研究者:Provides a regime-conditional test of LLM sentiment overlays on energy price signals, useful for designing AI-driven climate-risk and transition analytics.
🏢実務担当者:Suggests that geopolitical sentiment signals are only useful in specific market regimes, informing energy procurement and hedging timing rather than disclosure work.
🏛政策担当者:Highlights that hydrocarbon shocks coincide with capital shifting toward renewables, supporting energy-security and transition-investment policy design.
📄 Abstract（原文）
Between 2020 and 2026, the global energy sector experienced unprecedented turbulence driven by the COVID-19 pandemic, supply chain disruptions, and geopolitical conflicts, reshaping fossil fuel price discovery and accelerating the clean energy transition. Because standalone mean-reversion oscillators like the Relative Strength Index (RSI) frequently fail during directional energy shocks, this study evaluates a data-driven hybrid decision framework integrating the RSI with the Average Directional Index (ADX) regime filter and an asymmetric geopolitical sentiment overlay quantified by Large Language Models (LLMs). Using hourly data (2020–2026) across 24 analytical cross-sections, we examine three fossil fuels—WTI crude oil, Brent crude oil, and Henry Hub natural gas—alongside NextEra Energy (NEE) as a renewable power generation proxy. Results show that the AI sentiment filter enhances performance selectively: the largest gains occur for natural gas in consolidation regimes and for WTI crude oil, whereas Win Rate and maximum drawdown do not improve systematically (H1 not fully supported). Effectiveness proves strongly regime-dependent (H2 confirmed), while evidence for sentiment asymmetry remains indirect (H3). Crucially, NEE exhibits superior resilience consistent with capital substitution toward clean energy during hydrocarbon shocks (H4 confirmed), informing energy economics, energy security, and decarbonisation policy.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202611.0851.v1first seen 2026-11-13 04:28:02
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