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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/116007


    Title: 加權範數最小變異數投資組合之實證應用：以台灣股市為例
    The Empirical Study of Weighted-Norm Minimum Variance Portfolios in Taiwan Stock Market
    Authors: 莊丹華
    Jhuang, Dan-Hua
    Contributors: 顏佑銘
    Yen, Yu-Min
    莊丹華
    Jhuang, Dan-Hua
    Keywords: 台灣50
    最小變異數投資組合
    加權懲罰範數
    Minimum variance portfolio
    Weighted-Norm penalty
    Date: 2017
    Issue Date: 2018-03-02 11:38:43 (UTC+8)
    Abstract: 資產配置問題與方法一直是投資人所關心之重要課題。藉由不同之建構投資組合的方法尋找資產的最適權重分配，可使得投資人對所持有資產的管理變得更容易且具效率。在這些方法當中，最小變異數投資組合可滿足追求風險極小化之需求。本文亦從此出發，探討一種特殊的最小變異數投資組合：加權範數最小變異數投資組合，並以台灣50作為實證資料，運用十個績效指標來衡量加權範數最小變異數投資組合、其他三種標竿投資組合與指數型基金台灣50之表現。

    結果發現本研究所選取之台灣市場資料在運用加權範數最小變異數投資組合下，確實可以打敗其他大部分投資組合以及台灣50基金，並且在以下兩論點與過往文獻之敘述一致：加入報酬限制條件無法改善績效、使用替代參數亦可提供相稱績效。
    The asset allocation problem has always been an important issue on which investors concern. It is easier and more efficient for investors to manage their assets through constructing their portfolios in different methods to find the most optimized weight of assets. This essay explores a special portfolio, Weighted-Norm Minimum Variance Portfolio (WNMVP), which can minimize the risks of investment, and use Taiwan stock market data to undertake empirical study.

    The research measured the performance of WNMVP, other three benchmark portfolios, and Taiwan Top 50 ETF (0050) by using ten indicators, bringing three findings. First, WNMVP performs better than most of other portfolios do. Second, adding estimated mean return vector into the WNMVP does not improve performances. Third, three alternative norm penalties provide comparable performance as parameters in WNMVP do. The second and third findings are consistence with previous literature.
    Reference: 1. 李振婷(2015)。最小變異數投資組合在台灣股市之運用。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。
    2. Brodie, J., Daubechies, I., De Mol, C., Giannone, D., and Loris, I. (2009) Sparse and stable Markowitz portfolios, Proceedings of the National Academy of Sciences of the United States of America 106, 12267–12272.
    3. Chopra, Vijay K., and Ziemba, William T. (1993) The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice, The Journal of Portfolio Management, 19, 6–11.
    4. DeMiguel, V., Garlappi, L., and Uppal, R. (2009) Optimal versus naive diversification: how inefficient is the 1/N portfolio strategy? Review of Financial Studies 22, 1915–1953.
    5. DeMiguel, V., Garlappi, L., Nogales, F. J., and Uppal, R. (2009) A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science 55, 798–812.
    6. Fan, J., Zhang, J., and Yu, K. (2012) Vast portfolio selection with gross-exposure constraints, Journal of the American Statistical Association 107, 592–606.
    7. Friedman, J., Hastie, T., Ho¨ fling, H., and Tibshirani, R. (2007) Pathwise coordinate optimization, Annals of Applied Statistics 1, 302–332.
    8. Jagannathan, R. and Ma, T. (2003) Risk reduction in large portfolios: why imposing the wrong constraints helps, Journal of Finance 58, 1651–1684.
    9. Ledoit, O. and Wolf, M. (2003) Improved estimation of the covariance matrix of stock returns with an application to portfolio selection, Journal of Empirical Finance 10, 603–621.
    10. Markowitz, H. (1952) Portfolio Selection, The Journal of Finance, 7, 77–91.
    11. Merton, R. C. (1980) On estimating the expected return on the market: An exploratory investigation, Journal of Financial Economics, 8, 323–361.
    12. Tibshirani, R. (1996) Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), 58, 267–288.
    13. Yen, Y. –M. and Yen, T. J. (2014) Solving norm constrained portfolio optimization via coordinate-wise descent algorithms, Computational Statistics and Data Analysis 76, 737–759.
    14. Yen, Y. –M. (2015) Sparse Weighted-Norm Minimum Variance Portfolios, Review of Finance, 20, 1259–1287.
    15. Zou, H. and Hastie, T. (2005) Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67, 301–320.
    Description: 碩士
    國立政治大學
    國際經營與貿易學系
    104351029
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104351029
    Data Type: thesis
    Appears in Collections:[Department of International Business] Theses

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