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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/145781


    Title: ESG基金成分股中加權範數懲罰函數的實證應用
    The Empirical Study of Weighted Norm Penalty Function in ESG Fund Constituent Stocks
    Authors: 黃怡穎
    Huang, Yi-Ying
    Contributors: 顏佑銘
    黃怡穎
    Huang, Yi-Ying
    Keywords: ESG基金
    ESG投資策略
    加權懲罰範數
    最小變異數投資組合
    Date: 2023
    Issue Date: 2023-07-06 16:30:18 (UTC+8)
    Abstract: 本研究旨在探討加權範數懲罰函數在ESG（Environmental, Social, Governance）基金成分股中的實證應用。近年來，永續議題愈趨備受重視，ESG在當今金融界更是受到廣泛關注，投資者越來越關心公司的環境和社會影響力以及治理結構。ESG基金作為集結符合特定永續標準的一種投資工具，將永續因素納入股票選擇過程，成為投資者實現永續和負責任投資目標的重要手段。
    本研究利用加權範數懲罰函數作為投資組合優化的方法，旨在探索如何最大程度地平衡投資組合的風險和報酬。加權範數懲罰函數是一種能夠結合投資者風險偏好和投資組合風險特徵的函數，通過對不同風險數據進行加權處理，可以更好地反映投資者的偏好和市場情況。
    本研究採用加權範數最小變異數投資組合方法建立投資策略模型，並與均等權重投資組合、全局最小變異數投資組合、無放空最小變異數投資組合三種基準投資組合策略進行十種績效指標的比較。此外，本研究將同時被六檔ESG基金中，四檔以上選中的成分股擷取出來，作為比較樣本資產。同時，考慮目標報酬限制條件和替代範數懲罰，對全樣本資產和比較樣本資產進行了相關研究。
    研究結果顯示，在全樣本期間，加權範數最小變異數投資組合策略在報酬率、夏普比率、確定性等價報酬和累積財富比率等指標上表現較好。此外，加入目標報酬限制條件和替代範數懲罰對投資組合的績效和風險產生明顯影響。在ESG基金成分股的選股中，加權範數懲罰函數提供了一種優化的方法，能夠幫助投資者在平衡風險和報酬的基礎上實現更好的投資結果。本研究結果對於ESG投資策略的制定和實踐具有重要的參考價值。
    Reference: 陳睦宜(2022)。加權範數懲罰函數之實證應用：以中美貿易戰前後期間之台灣5G供應鏈產業為例。未出版之碩士論文，國立政治大學，國際經營與貿易學系，台北。
    蔡宛廷(2022)。以範數懲罰函數建構之投資組合實證應用：以新冠肺炎區間為例。未出版之碩士論文，國立政治大學，國際經營與貿易學系，台北。
    Black, F., & Scholes, M. (1972). The Valuation of Option Contracts and a Test of Market Efficiency. The Journal of Finance, 27(2), 399-417.
    Hsu, J. W., & Kalesnik, V. (2017). The Harm in Selecting Funds That Have Recently Outperformed. Financial Analysts Journal, 73(2), 77-93.
    Lintner, J. (1975). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics, 47(1), 13-37.
    Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
    Markowitz, H., & Todd, P. (2000). Mean-variance-penalized (MVP) portfolios. Journal of Portfolio Management, 26(4), 45-54.
    Michaud, R. O. (1989). The Markowitz Optimization Enigma: Is `Optimized` Optimal? Financial Analysts Journal, 45(1), 31-42.
    Moy, R. L., & Scherer, K. A. (2006). Is the Equal-Weighted Portfolio Efficient? The Journal of Portfolio Management, 33(1), 97-102.
    Sharpe, W. F. (1966). Mutual Fund Performance. The Journal of Business, 39(1), 119-138.
    Sharpe, W. F. (1970). Portfolio Theory and Capital Markets. The Journal of Business, 43(2), 119-138.
    Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B (Methodological), 58(1), 267-288.
    Wong, W. K. (2018). The Global Minimum Variance Portfolio Revisited: Evidence from the Hong Kong Stock Market. Journal of Economic Studies, 45(2), 313-328.
    Xiong, J. X., Ibbotson, R. G., & Chen, P. (2004). Dynamic Asset Allocation with Ambiguous Return Predictability. The Journal of Business, 77(1), 95-128.
    Yen, H. R. (2015). A norm penalized regression framework for portfolio construction. Journal of Banking & Finance, 53, 71-80.
    Yen, Y. M. (2015). Sparse Weighted-Norm Minimum Variance Portfolios. Review of Finance, 20, 1259-1287.
    Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(2), 301-320.
    Description: 碩士
    國立政治大學
    國際經營與貿易學系
    110351015
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0110351015
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

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