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題名 以基本面與投資組合理論建構台灣股票市場最適資產配置
Using fundamental analysis with portfolio theory to construct the optimal asset allocation in Taiwan stock market
作者 于孟玉
Yu, Meng Yu
貢獻者 黃泓智
于孟玉
Yu, Meng Yu
關鍵詞 投資組合理論
MV模型
MCVaR模型
共變異數估計
Portfolio theory
MV model
MCVaR model
Covariance estimator
日期 2017
上傳時間 31-Jul-2017 11:01:26 (UTC+8)
摘要   台灣現在已進入高齡化社會,該怎麼在退休前為自己累積一份財富為一重要議題,而以往許多研究都只針對不同類型資產進行資產配置分析,因此本研究便對於其中的股票進行投資組合的配置。首先透過個股篩選,利用基本面財報單因子以及財務特徵指標找出具有潛力的個股,再根據馬可維茲投資組合理論,找出在平均數-變異數投資組合模型(Mean-Variance Portfolio Model;MV模型)與平均數-條件風險值(Mean-Conditional Value at Risk Portfolio Model;MCVaR模型)下的最適投資組合與最小風險投資組合,並透過不同穩健共變異數估計方法來改善樣本變異數估計的偏誤,希望能藉由此資產配置策略達到良好的投資績效。
  研究結果發現透過基本面選股後,不論是MV模型或MCVaR模型在資產配置上都有良好的效果,與等權重投資組合相比甚至可以達到兩倍的績效,而穩健共變異數估計中以Shrink估計表現最為優異,且發現MCD與MVE估計並不是一個能夠改善樣本估計的良好方法,最後提出最適投資組合在獲利性財務指標篩股下有最好的績效,夏普比率為1.4544,而最小風險投資組合在品質性財務指標篩股下有最好的績效,夏普比率為1.7933。
參考文獻 許偉倫,2011。穩健型投資組合建構與回溯測試之探討。碩士論文。
盧泰源,2016。最適化Smart Beta 策略組合型基金之應用—以台灣股票市場之交易策略研究。碩士論文。
Abarbanell, J. S., &Bushee, B. J. (1998). Abnormal returns to a fundamental analysis strategy. Accounting Review, 19-45.
Artzner, P., F. Delbaen, J. Eber, and D. Health, (1999), Coherent measure of Risk. Mathematical Finance, Vol.2, pp.95-121.
Brianton, G. (1998). Portfolio optimization. Risk Management and Financial Derivatives: A Guide to the Mathematics, 1st edition, Palgrave (trade), 4, 39-44.
Brinson, G. P., Singer, B. D., &Beebower, G. L. (1991). Determinants of portfolio performance II: An update. Financial Analysts Journal, 40-48.
DeMiguel, V., & Nogales, F. J. (2009). Portfolio selection with robust estimation. Operations Research, 57(3), 560-577.
Graham, B., & Dodd, D. L. (1934). Security analysis: Principles and technique. McGraw-Hill.
Grubel, H. G. (1968). Internationally diversified portfolios: welfare gains and capital flows. The American Economic Review, 58(5), 1299-1314.
Ledoit, O., & Wolf, M. (2003). Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Journal of empirical finance, 10(5), 603-621.
Lev, B., &Thiagarajan, S. R. (1993). Fundamental information analysis. Journal of Accounting research, 190-215.
Li, D., & Ng, W. L. (2000). Optimal dynamic portfolio selection: Multiperiod mean‐variance formulation. Mathematical Finance, 10(3), 387-406.
Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
Ou, J. A., & Penman, S. H. (1989). Financial statement analysis and the prediction of stock returns. Journal of accounting and economics, 11(4), 295-329.
Pflug, G. C. (2000). Some remarks on the value-at-risk and the conditional value-at-risk. In Probabilistic constrained optimization (pp. 272-281). Springer US.
Rockafellar, R. &Uryasev, S. (2000). Optimization of conditional value-at-risk. The Journal of Risk, 2(3), 21–41.
Rousseeuw, P. J. (1985). Multivariate estimation with high breakdown point. Mathematical statistics and applications, 8, 283-297.
Rousseeuw, P. & Van Driessen, K. (1999). A fast algorithm for the minimumcovariance determinant estimator. Technometrics, 41, 212–223.
Rousseeuw, P., Croux, C., Todorov, V., Ruckstuhl, A., Salibian-Barrera, M., Verbeke, T., & Maechler, M. (2008). The robustbase package: Basic Robust Statistics. cran.r-project.org.
Schaefer, J., Opgen-Rhein, R., & Strimmer, K. (2008). The corpcor package:Efficient Estimation of Covariance and (Partial) Correlation. cran.r-project.org.
Sloan, R. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings? Accounting review, 71(3), 289-315.
Venables, W. N. & Ripley, B. D. (2008). The MASS Package. cran.r-project.org.
描述 碩士
國立政治大學
風險管理與保險學系
104358017
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104358017
資料類型 thesis
dc.contributor.advisor 黃泓智zh_TW
dc.contributor.author (Authors) 于孟玉zh_TW
dc.contributor.author (Authors) Yu, Meng Yuen_US
dc.creator (作者) 于孟玉zh_TW
dc.creator (作者) Yu, Meng Yuen_US
dc.date (日期) 2017en_US
dc.date.accessioned 31-Jul-2017 11:01:26 (UTC+8)-
dc.date.available 31-Jul-2017 11:01:26 (UTC+8)-
dc.date.issued (上傳時間) 31-Jul-2017 11:01:26 (UTC+8)-
dc.identifier (Other Identifiers) G0104358017en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111463-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 風險管理與保險學系zh_TW
dc.description (描述) 104358017zh_TW
dc.description.abstract (摘要)   台灣現在已進入高齡化社會,該怎麼在退休前為自己累積一份財富為一重要議題,而以往許多研究都只針對不同類型資產進行資產配置分析,因此本研究便對於其中的股票進行投資組合的配置。首先透過個股篩選,利用基本面財報單因子以及財務特徵指標找出具有潛力的個股,再根據馬可維茲投資組合理論,找出在平均數-變異數投資組合模型(Mean-Variance Portfolio Model;MV模型)與平均數-條件風險值(Mean-Conditional Value at Risk Portfolio Model;MCVaR模型)下的最適投資組合與最小風險投資組合,並透過不同穩健共變異數估計方法來改善樣本變異數估計的偏誤,希望能藉由此資產配置策略達到良好的投資績效。
  研究結果發現透過基本面選股後,不論是MV模型或MCVaR模型在資產配置上都有良好的效果,與等權重投資組合相比甚至可以達到兩倍的績效,而穩健共變異數估計中以Shrink估計表現最為優異,且發現MCD與MVE估計並不是一個能夠改善樣本估計的良好方法,最後提出最適投資組合在獲利性財務指標篩股下有最好的績效,夏普比率為1.4544,而最小風險投資組合在品質性財務指標篩股下有最好的績效,夏普比率為1.7933。
zh_TW
dc.description.tableofcontents 第一章 緒論 6
第一節 研究背景 6
第二節 研究目的 8
第三節 研究架構 10
第二章 文獻探討 11
第一節 基本面文獻探討 11
第二節 風險衡量指標文獻探討 12
第三節 投資組合理論文獻探討 14
第三章 研究方法 18
第一節 基本面單因子介紹 19
第二節 財務特徵指標介紹 20
第三節 投資組合理論介紹 21
第四章 實證結果分析 29
第一節 實證分析資料來源與說明 29
第二節 績效指標說明 29
第三節 投資組合績效分析 31
第五章 結論與未來方向建議 58
第一節 結論 58
第二節 未來方向建議 59
參考文獻 60
附錄 62
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104358017en_US
dc.subject (關鍵詞) 投資組合理論zh_TW
dc.subject (關鍵詞) MV模型zh_TW
dc.subject (關鍵詞) MCVaR模型zh_TW
dc.subject (關鍵詞) 共變異數估計zh_TW
dc.subject (關鍵詞) Portfolio theoryen_US
dc.subject (關鍵詞) MV modelen_US
dc.subject (關鍵詞) MCVaR modelen_US
dc.subject (關鍵詞) Covariance estimatoren_US
dc.title (題名) 以基本面與投資組合理論建構台灣股票市場最適資產配置zh_TW
dc.title (題名) Using fundamental analysis with portfolio theory to construct the optimal asset allocation in Taiwan stock marketen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 許偉倫,2011。穩健型投資組合建構與回溯測試之探討。碩士論文。
盧泰源,2016。最適化Smart Beta 策略組合型基金之應用—以台灣股票市場之交易策略研究。碩士論文。
Abarbanell, J. S., &Bushee, B. J. (1998). Abnormal returns to a fundamental analysis strategy. Accounting Review, 19-45.
Artzner, P., F. Delbaen, J. Eber, and D. Health, (1999), Coherent measure of Risk. Mathematical Finance, Vol.2, pp.95-121.
Brianton, G. (1998). Portfolio optimization. Risk Management and Financial Derivatives: A Guide to the Mathematics, 1st edition, Palgrave (trade), 4, 39-44.
Brinson, G. P., Singer, B. D., &Beebower, G. L. (1991). Determinants of portfolio performance II: An update. Financial Analysts Journal, 40-48.
DeMiguel, V., & Nogales, F. J. (2009). Portfolio selection with robust estimation. Operations Research, 57(3), 560-577.
Graham, B., & Dodd, D. L. (1934). Security analysis: Principles and technique. McGraw-Hill.
Grubel, H. G. (1968). Internationally diversified portfolios: welfare gains and capital flows. The American Economic Review, 58(5), 1299-1314.
Ledoit, O., & Wolf, M. (2003). Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Journal of empirical finance, 10(5), 603-621.
Lev, B., &Thiagarajan, S. R. (1993). Fundamental information analysis. Journal of Accounting research, 190-215.
Li, D., & Ng, W. L. (2000). Optimal dynamic portfolio selection: Multiperiod mean‐variance formulation. Mathematical Finance, 10(3), 387-406.
Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
Ou, J. A., & Penman, S. H. (1989). Financial statement analysis and the prediction of stock returns. Journal of accounting and economics, 11(4), 295-329.
Pflug, G. C. (2000). Some remarks on the value-at-risk and the conditional value-at-risk. In Probabilistic constrained optimization (pp. 272-281). Springer US.
Rockafellar, R. &Uryasev, S. (2000). Optimization of conditional value-at-risk. The Journal of Risk, 2(3), 21–41.
Rousseeuw, P. J. (1985). Multivariate estimation with high breakdown point. Mathematical statistics and applications, 8, 283-297.
Rousseeuw, P. & Van Driessen, K. (1999). A fast algorithm for the minimumcovariance determinant estimator. Technometrics, 41, 212–223.
Rousseeuw, P., Croux, C., Todorov, V., Ruckstuhl, A., Salibian-Barrera, M., Verbeke, T., & Maechler, M. (2008). The robustbase package: Basic Robust Statistics. cran.r-project.org.
Schaefer, J., Opgen-Rhein, R., & Strimmer, K. (2008). The corpcor package:Efficient Estimation of Covariance and (Partial) Correlation. cran.r-project.org.
Sloan, R. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings? Accounting review, 71(3), 289-315.
Venables, W. N. & Ripley, B. D. (2008). The MASS Package. cran.r-project.org.
zh_TW