政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/155529
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 114396/145431 (79%)
造访人次 : 53068971      在线人数 : 610
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/155529


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/155529


    题名: 台灣股市中市場資訊交互預測新視角
    A New Perspective on the Cross-Predictability of Market Information in Taiwan Stock Market
    作者: 林祥恩
    Lin, Hsiang-En
    贡献者: 羅秉政
    Kendro Vincent
    林祥恩
    Lin, Hsiang-En
    关键词: 交互預測
    主投資組合分析
    市場資訊
    異常投資組合
    Cross-Predictability
    Principal Portfolio Analysis
    Market Information
    Anomaly Portfolio
    日期: 2024
    上传时间: 2025-02-04 16:20:00 (UTC+8)
    摘要: 本研究運用主投資組合分析方法，探討以市場資訊建構之異常投資組合的交互預測能力及其對投資績效的影響。實證結果顯示，融入交互預測的投資組合在 Sharpe Ratio 上顯著超越基準投資組合。其中，主非對稱投資組合的 Sharpe Ratio 高達 0.63，且因子迴歸估計中具有顯著的 Fama-French 五因子模型 alpha 值 1.20%，表明其具備提升風險調整後報酬的能力。此外，分析顯示預期報酬率的排序未必完全反映實際表現，操作策略應綜合考量不同的主投資組合，以提升穩健性與潛在報酬。本研究為異常投資組合交互預測的應用提供了實證支持，並為投資策略優化提供參考。
    This study utilizes Principal Portfolio Analysis to investigate the cross-predictability of anomaly portfolios constructed from market information and its implications for investment performance. Empirical results reveal that portfolios integrating cross-predictability significantly outperform the benchmark portfolio in terms of Sharpe Ratio. Notably, the principal alpha portfolio achieves a Sharpe Ratio of 0.63, with a statistically significant Fama-French 5 factor alpha of 1.20%, highlighting its superior capability in enhancing risk-adjusted returns. Furthermore, the findings indicate that the ranking of expected returns may not always align with actual performance, suggesting that investment strategies should integrate multiple principal portfolios to improve robustness and potential profitability. This study provides empirical evidence for the utility of cross-predictability in anomaly portfolios and offers practical insights for optimizing investment strategies.
    參考文獻: Bui, D. G., Kong, D.-R., Lin, C.-Y., and Lin, T.-C. (2023). Momentum in machine
    learning: Evidence from the Taiwan stock market. Pacific-Basin Finance Journal,
    82:102178.
    Cakici, N., Fieberg, C., Metko, D., and Zaremba, A. (2024). Do anomalies really predict
    market returns? New data and new evidence. Review of Finance, 28(1):1–44.
    Dong, X., Li, Y., Rapach, D. E., and Zhou, G. (2022). Anomalies and the expected market
    return. The Journal of Finance, 77(1):639–681.
    Du, D., Huang, Z., and Liao, B.-S. (2009). Why is there no momentum in the Taiwan
    stock market? Journal of Economics and Business, 61(2):140–152.
    Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of
    Financial Economics, 116(1):1–22.
    George, T. J. and Hwang, C.-Y. (2004). The 52-week high and momentum investing. The
    Journal of Finance, 59(5):2145–2176.
    Gu, S., Kelly, B., and Xiu, D. (2020). Empirical asset pricing via machine learning. The
    Review of Financial Studies, 33(5):2223–2273.
    Kelly, B., Malamud, S., and Pedersen, L. H. (2023). Principal portfolios. The Journal of
    Finance, 78(1):347–387.
    Lin, C., Ko, K.-C., and Yang, N.-T. (2022). Does the momentum gap explain momentum
    in Taiwan? Pacific-Basin Finance Journal, 72:101732.
    Yan, J. and Yu, J. (2023). Cross-stock momentum and factor momentum. Journal of
    Financial Economics, 150(2):103716.
    描述: 碩士
    國立政治大學
    金融學系
    112352009
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0112352009
    数据类型: thesis
    显示于类别:[金融學系] 學位論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    200901.pdf26641KbAdobe PDF0检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈