博碩士論文 etd-0527113-113325 詳細資訊


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姓名 賴柏成(Po-Cheng Lai) 電子郵件信箱 E-mail 資料不公開
畢業系所 財務管理學系研究所(Finance)
畢業學位 碩士(Master) 畢業時期 102學年第1學期
論文名稱(中) 以財務報表資訊與Copula-GARCH模型建構投資組合-應用在台灣股票市場
論文名稱(英) Constructing Portfolios According to Financial Statement Information and Copula-GARCH Model in Taiwan Stock Market
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    紙本論文:5 年後公開 (2018-12-18 公開)

    電子論文:使用者自訂權限:校內 5 年後、校外 5 年後公開

    論文語文/頁數 中文/65
    統計 本論文已被瀏覽 5613 次,被下載 178 次
    摘要(中) 一直以來,如何選擇出好的股票都是一個深具挑戰性且重要的問題。要建構一個成功的投資組合必須仰賴可靠的選股策略,而隨著財務工程與資料探勘技術的發展,使得這個問題能夠更有效的被處理。本文以台灣股票市場為例,利用財務報表資訊及Zakamouline and Koekebakker (2009)所提出之經過偏態與峰態調整的Sharpe比率(Adjusted for skewness and kurtosis Sharpe ratio, ASKSR)來篩選股票,並以Copula-GARCH模型進行估計與蒙地卡羅模擬,最後利用預期效用函數最適化權重來建構投資組合,希望能建立一個系統化、數量化的選股模型,持續的擊敗大盤。
    本研究以台灣股票市場1998年至2012年之上市櫃公司為樣本,分別測試共六種不同樣本內、外期間長度組合之績效表現。實證結果發現以此方法建構之投資組合皆能顯著擊敗大盤,其中又以使用mean-variance效用函數與風險趨避係數γ=1之CRRA效用函數最適化權重之報酬最高。而加入市場風險中立策略後,可顯著改善投資組合的穩定性,降低投資組合價值受到金融海嘯衝擊所造成的劇烈下跌。此外,將投資期間分為10年、5年、3年等較短的子期間來測試此模型之穩健性,結果發現依此方法建構之投資組合仍然能維持優異表現,代表此方法並不只在某段特定期間有效,而是一個穩定且能持續執行的策略。
    摘要(英) Stock selection always has been a challenging and important task. This line of research is highly contingent upon reliable stock ranking for successful portfolio construction. Thanks to recent advances in financial engineering and data mining, we can solve these problems more effectively. In this study, we use financial statement information and the ASKSR proposed by Zakamouline and Koekebakker(2009) for stock selection. Furthermore, we apply Copula-GARCH model on Monte Carlo method to generate dynamic optimal weights based on expected utility function. According to this process, we try to construct a quantitative stock selection model which can consistently beat the market.
    We take all the listed companies in the Taiwan stock market over the period of 1998-2012 as our sample and examine the profitability of portfolios constructed by the combination of different length of in sample and out sample data. The empirical result shows that our portfolios can earn significantly higher return than the TAIEX Total Return Index, especially those that generate optimal weights by mean-variance utility function andγ=1 CRRA utility function. Moreover, after we applied market neutral strategy, we can significantly improve the stability of our portfolios and reduce the possibility of severe losses by the impact of financial crisis. Finally, a robustness test was built to validate if this method works well all the time. We divide our investment period into three shorter periods, and it turns out this method still have great performances on each of the shorter period. As a result, this portfolio construction strategy indeed can be applied consistently and effectively in Taiwan stock market.
    關鍵字(中)
  • 投資組合
  • 選股策略
  • 預期效用函數
  • GARCH
  • Copula
  • ASKSR
  • 關鍵字(英)
  • Portfolio
  • Stock Selection
  • Expected Utility Function
  • Copula
  • GARCH
  • ASKSR
  • 論文目次 論文審定書 i
    摘要 ii
    Abstract iii
    目錄 iv
    圖次 vi
    表次 vii
    第一章 緒論 1
    第一節 研究動機與目的 1
    第二節 研究架構 3
    第二章 文獻探討 4
    第一節 股價報酬決定因素 4
    第二節 Copula相關文獻 5
    第三章 研究方法 7
    第一節 股票篩選準則 7
    第二節 修正Sharpe比率 7
    第三節 多元Gaussian Copula模型 8
    第四節 邊際分配模型 10
    第五節 模型估計方法 10
    第六節 預期效用函數 11
    第四章 實證結果 13
    第一節 資料說明與處理 13
    第二節 投資組合績效分析 14
    第二節 市場中立策略 29
    第三節 穩健性測試 43
    第五章 結論與建議 45
    第一節 結論 45
    第二節 後續研究建議 46
    參考文獻 47
    附錄 50
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    口試委員
  • 唐俊華 - 召集委員
  • 蔡維哲 - 委員
  • 王昭文 - 指導教授
  • 黃振聰 - 指導教授
  • 口試日期 2013-06-16 繳交日期 2013-12-18

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