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| Title: | 氣候政策不確定性模擬投資組合之建構 — 以美國為例
Factor Mimicking Portfolios for Climate Policy Uncertainty: Evidence from the U.S. |
| Authors: | 蔡沛秦
Tsai, Pei-Chin |
| Contributors: | 羅秉政
Kendro Vincent
蔡沛秦
Tsai, Pei-Chin |
| Keywords: | 模擬投資組合
氣候政策不確定性
Factor-mimicking portfolio
Climate policy uncertainty |
| Date: | 2025 |
| Issue Date: | 2025-08-04 14:31:58 (UTC+8) |
| Abstract: | 本研究旨在探討氣候政策不確定性（Climate Policy Uncertainty, CPU）風險之避險策略，並延伸 Engle et al. (2020) 之 mimicking portfolio 方法，建構一組能有效對應 CPU 創新項（AR(1) 殘差）波動的模擬投資組合。本文分別採用 S&P Global 與 Sustainalytics 兩家 ESG 評分機構所提供之 ESG 分數作為企業特徵，建構多空投資組合。實證結果顯示，使用 S&P Global ESG 整體分數建構的模擬投資組合，其組成建議增加低 ESG 評分之資產、減少高 ESG 評分資產配置，能有效對應氣候不確定性衝擊所帶來的風險；相對地，以 Sustainalytics 分數構建之投資組合則難以穩定捕捉此一衝擊。在樣本外測試中，採用擴張視窗法（Expanding Window）所建構之模擬投資組合，其報酬與氣候政策不確定性指數的創新項之相關性最高可達約 10%，顯示此方法具備一定程度之避險能力。傳統因子特徵（如規模與價值）納入後則未顯著提升整體表現。進一步採用 Bai-Perron 測試發現，CPU 指數於 2016 年 11 月川普當選時出現結構性變動，將樣本區分為川普當選前後進行子樣本分析，顯示政權更替後避險效果更為穩健。此外，本文亦延伸採用公司層級氣候風險指標作為特徵進行測試，惟其避險表現整體仍不及 S&P Global ESG 分數。
This study explores hedging strategies against Climate Policy Uncertainty(CPU) risks by extending the mimicking portfolio approach of Engle et al.(2020). We construct long-short portfolios based on ESG scores from S&P Global and Sustainalytics, aiming to track the innovations (AR(1) residuals) of the CPU index. Empirical results show that portfolios formed using S&P Global scores—by overweighting brown assets—can better hedge CPU shocks, while those based on Sustainalytics perform less consistently. Using an expanding window method, the out-of-sample correlation with CPU innovations reaches up to 10%, suggesting moderate hedging effectiveness. A structural break is detected in November 2016, coinciding with Trump’s election, after which hedging performance improves notably. We further test alternative firm-level climate risk measures, but S&P Global ESG scores remain the most robust and representative characteristics for constructing CPU hedging portfolios. |
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| Description: | 碩士
國立政治大學
金融學系
112352008 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112352008 |
| Data Type: | thesis |
| Appears in Collections: | [金融學系] 學位論文
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