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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/76838


    Title: 最小變異數投資組合在台灣股市之運用
    The Empirical Study of Performance of Minimum Variance Portfolio in Taiwan Stock Market
    Authors: 李振婷
    Contributors: 郭維裕
    李振婷
    Keywords: 最小變異數投資組合
    滾動視窗
    市值加權投資組合
    Date: 2015
    Issue Date: 2015-07-27 11:18:04 (UTC+8)
    Abstract: 市值加權的投資組合方式一直廣為投資者所接受，其誘人之處莫過於集合前幾大市值的公司，並依據市值加權分配權重。在Markowitz(1952)提出的投資理論基礎下，討論了能夠在最小風險下獲得較高的預期報酬，應用在資產配置上即為最小變異數投資組合的投資策略。此觀念出現時，造成了市值加權投資組合其投資效率性受到質疑；由於影響市場變動的因子複雜性高，報酬率並不容易預測，因此出現了不少以最小風險為主要投資目標，而非追求高的預期報酬為主要目的之投資觀點。
    本研究以市值加權投資組合為比較對象，探討最小變異數投資組合是否為更有效率的投資組合。以台灣50為市值加權投資組合，運用台灣50資料以滾動視窗的方式估計出最小變異數之權重，以此為最小變異數投資組合，比較兩者間的投資報酬率、績效表現。此外，本研究也將同時探討3種滾動視窗的期間長短，配合4種權重持有時間策略，以期了解參考資訊的時間長短、以及持有權重長短的策略是否會影響最小變異數投資組合的報酬率表現；最後，再運用迴歸分析，了解最小變異數投資組合與Fama-French三因子和動能因子之間的關聯性。
    研究結果指出，當參考資訊越長期的滾動視窗估計方式，最小變異數投資組合會有較穩定的投資報酬率；若搭配長期的權重持有期間，能運用在長期投資。欲投資短期則可運用滾動視窗較短的估計方式，其在更新資訊較迅速的優勢之下，擁有較極端的報酬率的機率大，同時績效表現也較佳，此也代表最小變異數投資組合的權重估計若適當，則報酬率表現相當傑出；反之則有相當可觀的損失。觀察影響因子層面，最小變異數投資組合主要受到市場溢酬因子的影響，但根據短期權重持有的策略來說，則是動能因子影響越趨顯著。
    Reference: Arnott, R. D., 2004, “Blinded by Theory: How Finance Theory Leads Us Astray,” Journal of Portfolio Management, vol. 30, no. 5, Thirtieth Anniversary Edition: 113-123.
    Arnott, R. D., J. C. Hsu and P. Moore., 2005, “Fundamental Indexation,” Financial Analysts Journal, vol. 61, no. 2, March/April: 83-99.
    Arnott, R. D., F. Li and K. Sherrerd., 2009a., “Clairvoyant Value and the Value Effect,” Journal of Portfolio Management, vol. 35, no. 3, spring: 12-26.
    Arnott, R. D., F. Li and K. Sherrerd., 2009b, “Clairvoyant Value II: The Growth/Value Cycle,” Journal of Portfolio Management, vol. 35, no. 4, Summer: 142-157.
    Bernd S., 2010, “ A New Look At Minimum Variance Investing,” Available at SSRN: http://ssrn.com/abstract=1681306
    Choueifaty, Y and Y. Coignard., 2008,“Toward Maximum Diversification,” Journal of Portfolio Management, vol. 35, no. 1, fall.
    Falkenstein, Eric G., 2009,“Risk and Return in General: Theory and Evidence,” Available at SSRN: http://ssrn.com/abstract=1420356
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    Robert D. Arnott, J. C. Hsu, and P. Moore, 2005,“Fundamental Indexation”, Financial Analysts Journal, Vol. 61, No. 2, pp. 83-99, March/April 2005
    Roger G Clarke, H. De Silva, and S.Torley, 2010,“Minimum Variance Portfolio Composition”, Journal of Portfolio Management, Vol. 37, No. 2, pp. 31-45 (Winter 2011)
    Roger G.C., H. De Silva, S. Torley, 2012,“Risk Parity, Maximum Diversification, and
    Minimum Variance: An Analytic Perspective”, Journal of Portfolio Management, 39(3):39-53, 2013
    Rob A., V. Kalesnik, P. Moghtader and C. Scholl., 2010, “Beyond Cap Weight, The empirical evidence for a diversified beta”, Journal of Index, January/February 2010
    T. Chow, J. C. Hsu Ph.D., Li-lan Kuo, and F.Li Ph.D, 2013. “A Survey of Low Volatility Strategies”., Available at SSRN: http://ssrn.com/abstract=2298117
    Victor De M., L. Garlappi, and R. Uppal., 2007.,“Optimal Versus Naïve Diversification:How Inefficient is the 1/N Portfolio Strategy?. Published by Oxford University Press on behalf of The Society for Financial Studies.
    Description: 碩士
    國立政治大學
    國際經營與貿易研究所
    102351034
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102351034
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

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