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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/86217


    Title: 價值投資策略在美國股市之應用;Applications of Value Investment Strategy in the U.S. Stock Market
    Authors: 王琪玲;Wang, Chyi Ling
    Contributors: 財務金融學系在職專班
    Keywords: 價值投資策略;資本報酬率;盈餘殖利率;美股投資;Value Investment Strategy;Return on Capital;Earning Yields;U.S. Stock Investment
    Date: 2021-07-28
    Issue Date: 2021-12-07 12:17:53 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究為以資本報酬率(Return on capital)與盈餘殖利率(Earnings Yield)兩項指標,作為選股指標,並以Compustat資料庫2000年至2019年美國上市公司市值前500大個股財報與股價資料進行回測分析。
    研究實證,以資本報酬率、盈餘殖利率為指標建構之投資組合,進行績效結果分析與回測,其投資策略之個股排序效果確實存在;經綜合分數累計較佳之個股組成之投資組合,投資報酬率較佳且風險波動度低。同時,此選股策略採不同投資時點、不同投資區間,並增加樣本家數回測,其績效結果亦同。
    本研究同時發現,當投資策略初期形成漲多態勢,投資績效較顯著。故常及時更新選股指標之「季」投資策略,會較以「年」為區間的投資策略獲利績效較為顯著。
    ;This study uses return on capital and earnings yield as the two indicators for stock selection. It also utilizes financial reports and stock prices of the top 500 U.S. listed companies by market capitalization collected from the Compustat database in 2000-2019 to perform a backtest analysis.
    By using performance analysis and backtesting, this paper shows evidence of using return on capital and earnings yield as indicators, and the consideration of investment strategy and stock rankings when building an investment portfolio. A portfolio that consists of stocks with high aggregate scores had the best return on investment with low risk volatility. At the same time, this stock selection strategy adopted different investment periods and trading ranges, and also increased sample size for backtest analysis and the results were the same.
    This paper finds that in the early stages of the investment strategy, there is an upward trend and the highest returns. Therefore, given that the stock selection indicators are updated regularly, a quarterly investment strategy will yield a better return than a yearly investment strategy.
    Appears in Collections:[Executive Master of Finance Management] Electronic Thesis & Dissertation

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