跳到主要內容

簡易檢索 / 詳目顯示

研究生: 趙國安
Guo-An Chao
論文名稱: 隨機優越動能策略-以台灣股票市場為例
Construct stochastic dominance momentum strategy
指導教授: 黃瑞卿
Rachel Juiching Huang
葉錦徽
Jin-Huei Yeh
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 財務金融學系
Department of Finance
論文出版年: 2017
畢業學年度: 105
語文別: 中文
論文頁數: 32
中文關鍵詞: 隨機優越動能策略
外文關鍵詞: stochastic dominance, momentum strategy
相關次數: 點閱:12下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本文藉由二階隨機優越 (Second-Degree Stochastic Dominance, SSD) 與1.5階隨機優越 (1.5-Degree Stochastic Dominance, 1.5SD) 法則篩選出SD贏家與SD輸家之股票,並且檢測買進SD贏家與賣出SD輸家的套利投資組合是否有顯著超額報酬。隨機優越不像平均數-變異數 (mean-variance)需要假設特定之報酬分配或者效用函數,僅以過去報酬率排序的方式判斷風險性資產之優越性,並且不同於動能策略,隨機優越有著理論的支持。
    實證結果發現,藉由過去6個月形成期為基礎,不論利用二階隨機優越法則或1.5階隨機優越法則選出的SD贏家投資組合皆有顯著的額外報酬,並且買進SD贏家放空SD輸家之套利投資組合無論持有期為3個月、6個月、9個月或是12個月,超額報酬皆為正值。除此之外,此超額報酬使用CAPM單因子、Fama-French三因子以及Carhart四因子迴歸模型皆無法圓滿解釋。


    In this paper, we construct SD-winner and SD-loser portfolios based on 1.5 and second degree stochastic dominance rules and examine the performance of arbitrage portfolio which by longing SD-winner stocks and short selling SD-loser stocks. Compared with the most widely accepted Mean-Variance framework, SD rules require neither a specific return distribution nor a specific utility function. SD rules just need to determine SD-winner or SD-loser on ranking previous 6-month returns.
    In empirical test, we form portfolios through the previous 6-month ranking period and hold them up to 12 months.
    The results show that SD-winner portfolios produce statistically, significant abnormal returns and arbitrage portfolio has positive excess return. Moreover, these returns are robust with respect to the single index CAPM, the Fama-French three-factor model, the Carhart four-factor model under various criteria of the SD investment strategy.

    目次 摘要 I ABSTRACT II 目次 III 圖目錄 IV 表目錄 V 第一章 緒論 1 第二章 隨機優越法則 4 2.1 一階隨機優越法則 (FSD) 4 2.2 二階隨機優越法則 (SSD) 5 2.3 一階隨機優越與二階隨機優越之間 5 第三章 資料與研究方法 7 第四章 實證結果與分析 10 4.1 隨機優越投資組合之報酬 10 4.2 套利投資組合超額報酬之檢定 11 4.3 穩健性測試 12 第五章 結論 13 參考文獻 22

    Babbel, D.F., & Herce, M.A., 2007. A closer look at stable value funds performance. Working
    Paper, 07-21.

    Clark, E., & K. Kassimatis (2014). Exploiting stochastic dominance to generate
    abnormal stock returns. Journal of Financial Markets, (20), 20-38.

    Carhart, M. M. (1997). On persistence in mutual fund performance. The Journal of finance,
    52(1), 57-82.

    Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. The journal of finance, 51(1), 55-84.

    George, T. J., Hwang, C. Y., The 52-Week High and Momentum Investing. Journal of Finance, (59)5, 2145-2176.

    Hadar, J., & Russell, W. R. (1971). Stochastic dominance and diversification.
    Journal of Economic Theory, 3(3), 288-305.

    Hanoch, G., & Levy, H. (1969). The efficiency analysis of choices involving risk. The
    Review of Economic Studies, 36(3), 335-346.

    Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications
    for stock market efficiency. The journal of finance, 48(1), 65-91.

    Levy, H., & Markowitz, H. M. (1979). Approximating expected utility by a function of mean and variance. The American Economic Review, 69(3), 308-317.

    Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.

    Markowitz, H. (1952). The utility of wealth. Journal of Political Economy, 60(2), 151-158.

    Müller, A., & Scarsini, M., & Tsetlin, I., & Winkler, R. (2016). Between First- and Second
    Order Stochastic Dominance, Management Science, Articles in Advance, 1-16.

    Rothschild, M., & Stiglitz, J. E. (1970). Increasing risk: I. A definition. Journal of Economic theory, 2(3), 225-243.

    QR CODE
    :::