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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97548完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳彥行 | zh_TW |
| dc.contributor.advisor | Yang-Shing Chen | en |
| dc.contributor.author | 江淙安 | zh_TW |
| dc.contributor.author | Tsung-An Chiang | en |
| dc.date.accessioned | 2025-07-02T16:24:43Z | - |
| dc.date.available | 2025-07-03 | - |
| dc.date.copyright | 2025-07-02 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-06-16 | - |
| dc.identifier.citation | Andersson, M., Bolton, P., and Samama, F. (2016). Hedging climate risk. Financial Analysts Journal, 72(3), 13–32.
Blitz, D., Chen, M., Howard, C., and Lohre, H. (2024). 3D investing: Jointly optimizing return, risk, and sustainability. Financial Analysts Journal, 80(3), 59–75. Bolton, P., and Kacperczyk, M. (2021). Do investors care about carbon risk? Journal of Financial Economics, 142(2), 517–549. Bolton, P., Kacperczyk, M. and Samama, F. (2022). Net-zero carbon portfolio alignment. Financial Analysts Journal, 78(2), 19–33. Busch, T., and Hoffmann, V. H. (2011). How hot is your bottom line? Linking carbon and financial performance. Business and Society, 50(2), 233–265. Dietz, S., Bowen, A., Dixon, C., and Gradwell, P. (2016). ‘Climate value at risk’ of global financial assets. Nature Climate Change, 6(7), 676–679. Kalesnik, V., Wilkens, M. and Zink, J. (2020). Green data or greenwashing? Do corporate carbon emissions data enable investors to mitigate climate change? SSRN Electronic Journal. Khan, M., Serafeim, G., and Yoon, A. (2016). Corporate sustainability: First evidence on materiality. The accounting review, 91(6), 1697–1724. Krueger, P., Sautner, Z., and Starks, L. T. (2020). The importance of climate risks for institutional investors. Review of Financial Studies, 33(3), 1067–1111. Lee, S. Y., and Kim, Y. H. (2015). Antecedents and consequences of firms’ climate change management practices: Stakeholder and synergistic approach. Sustainability, 7(11), 14521–14536. Le Guenedal, T. and Roncalli, T. (2022). Portfolio construction with climate risk measures. Available at SSRN 3999971. Le Guenedal, T., Lombard, F., Roncalli, T. and Sekine, T. (2022). Net zero carbon metrics. Available at SSRN 4033686. Lee, H., Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., ... and Park, Y. (2023). IPCC, 2023: Climate Change 2023: Synthesis Report, Summary for Policymakers. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland. Markowitz, H. (1952). Modern portfolio theory. Journal of Finance, 7(11), 77–91. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97548 | - |
| dc.description.abstract | 本研究針對臺灣市值前50大上市公司，建構符合1.5°C減碳路徑的低碳投資組合。透過三種方法預測2024年企業範疇一與二碳排放，並以非線性規劃模型求解投組權重，在兼顧與台灣50報酬指數的追蹤誤差的情況下，實現投組年度減碳4%目標。本研究發現企業在永續報告書中揭露的減碳路徑最適合作為建議投組時預測該年度碳排量的方式，根據此預測方式所建立的投組在2024和2025年分別減碳4%下，追蹤誤差為4.08%，兼顧業界對於投組績效偏離標竿指數的容忍程度與減碳。 | zh_TW |
| dc.description.abstract | This study focuses on the top 50 listed companies by market capitalization in Taiwan, constructing a low-carbon investment portfolio aligned with a 1.5°C decarbonization pathway. Three methods are employed to forecast corporate Scope 1 and Scope 2 carbon emissions for 2024, and a nonlinear programming model is used to determine portfolio weights. This approach achieves an annual portfolio decarbonization target of 4% while managing tracking error relative to the Taiwan 50 Index. The study finds that the decarbonization pathways disclosed in corporate sustainability reports are the most suitable for predicting annual carbon emissions when recommending investment portfolios. Based on this prediction method, the resulting portfolio achieves a 4% decarbonization in both 2024 and 2025, with a tracking error of 4.08%, balancing industry tolerance for performance deviation from the benchmark index with decarbonization goals. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-07-02T16:24:43Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-07-02T16:24:43Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 摘要 i
Abstract ii 目次 iii 圖次 iv 表次 iv 第一章 緒論 1 第二章 研究方法 4 2.1樣本選取和預測方法 4 2.2模型建置 7 第三章 實證結果與分析 8 3.1預測方法分析 8 3.2預測投組總碳排方法的回測分析 11 第四章 結論 13 參考文獻 14 附錄 26 圖1 對地球升溫影響1.5℃規劃路徑(各情境) 15 圖A1 2023年聯發科永續報告書節錄(以碳排量為減碳目標) 27 圖A2 2023年亞德客-KY永續報告書節錄(以碳強度為減碳目標) 27 圖A3 2023年上海商銀永續報告書節錄(預計於2025年才提出目標) 27 表1 碳排預測方法說明 16 表2不同升溫情境下方法二的減碳路徑 17 表3方法一預測中各子方法使用的公司數量統計 18 表4 投組總碳排整理 19 表5 TE結果整理 20 表6 實證結果_假設2024年個股碳排與2023年相同不變(減4%路徑) 21 表7 實證結果_使用方法一預估2024年個股碳排(減4%路徑) 22 表8 投組總碳排回測結果 23 表9 方法一回測_低估公司 24 表10 方法一回測_高估公司 25 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 低碳投資、碳排放預測、追蹤誤差、1.5°C減碳路徑、投組優化 | zh_TW |
| dc.subject | Portfolio optimization | en |
| dc.subject | Low-carbon investment | en |
| dc.subject | Carbon emission forecasting | en |
| dc.subject | Tracking error | en |
| dc.subject | 1.5°C decarbonization pathway | en |
| dc.title | 台灣50成分股之淨零碳排放目標投資組合設計 | zh_TW |
| dc.title | Constructing a Net-Zero Aligned Investment Portfolio Based on the Taiwan 50 Index Constituents | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳宗岡;蔡宜均 | zh_TW |
| dc.contributor.oralexamcommittee | Tsung-Kang Chen;Yi-Chun Tsai | en |
| dc.subject.keyword | 低碳投資、碳排放預測、追蹤誤差、1.5°C減碳路徑、投組優化, | zh_TW |
| dc.subject.keyword | Low-carbon investment, Carbon emission forecasting, Tracking error, 1.5°C decarbonization pathway, Portfolio optimization, | en |
| dc.relation.page | 27 | - |
| dc.identifier.doi | 10.6342/NTU202501121 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-06-17 | - |
| dc.contributor.author-college | 管理學院 | - |
| dc.contributor.author-dept | 財務金融學系 | - |
| dc.date.embargo-lift | 2025-07-03 | - |
| 顯示於系所單位： | 財務金融學系 | |
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