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研究生: 尤耀駒
Yo, Yao-Jyu
論文名稱: 產業動能策略與動能生命週期假說的實證 -以臺灣市場為例
An Empirical Study on Industry Momentum Strategy and Momentum Life Cycle Hypothesis – Evidence from the Taiwan Stock Market
指導教授: 顏盟峯
Yen, Meng-Feng
學位類別: 碩士
Master
系所名稱: 管理學院 - 財務金融研究所
Graduate Institute of Finance
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 40
中文關鍵詞: 反應不足動能策略產業動能動能生命週期假說
外文關鍵詞: Momentum Trading, Industry Momentum, Momentum Life Cycle
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  • 「產業輪動,個股表現」是臺灣股票市場上時常聽到的一段話;雖然買進過去 表現好的股票、放空過去績效差的股票乍看是個沒做作業的懶人投資法,但自 Jegadeesh and Titman (1993) 提出「動能交易策略」以降,認為投資人對於資訊的反 應普遍存在反應不足的現象,使得以各式各樣指標所形成的「買贏家賣輸家」之動 能策略有如過江之鯽,舉凡營收動能、盈餘動能、移動平均線動能、近期 52 週高價 動能、殘差動能...等,不勝枚舉。本文在觀察臺灣股票市場總流傳著「選產業!選 產業!」的主流邏輯下,探討由 Moskowitz and Grinblatt (1999) 提出的產業動能交 易策略於臺灣市場的實證性,並結合 Lee and Swaminathan (2000) 建立的「動能生命 週期假說 (Momentum Life Cycle, MLC)」,嘗試將交易量變數做為動能策略中的一道 濾網,測試所謂「新手看價,老手看量」是否的確是市場上獲得超額報酬的交易者 的共同特徵。本文參考 MLC,建立「買進過去績效好且平均交易量低、放空過去績 效差且平均交易量高」之「早期投組 (Early Momentum Strategy, EMS)」,以及在交 易量濾網上相反策略的「晚期投組 (Late Momentum Strategy, LMS)」,進行績效策略 的分析與比較,以界定當考量交易量變數之後,何者為較佳的改良策略。研究結果 顯示,早期投組可明顯創造優於原始純粹動能投組更為優異且穩健的報酬,而晚期 投組的績效雖顯著,但卻無法改良原始純粹動能投組。MLC 在臺灣市場以產業動能 策略的實證結果建議在執行如斯操作時,交易量所提供的訊息並非平常熟知的越高 越好,而是透過交易量的過濾,找尋出呈現早期動能的標的,提早全市場進行買進 或放空,獲取更多的超額報酬。

    Since Jegadeesh and Titman (1993) found evidence from the U.S. market that the “Buy winner, Sell loser” strategy, also known as “Momentum Trading Strategy” is significantly profitable, there have been a plenty of research focused on the development of different kinds of momentum, such as sales momentum, earnings momentum, moving average momentum, recent 52-week high momentum, residual momentum, etc. Moskowitz and Grinblatt (1999) propose the theory of industry momentum, arguing that the relatively strong industries in the past tend to perform strongly in the future whereas relatively weak industries in the past tend to perform poorly in the future. In light of the well-known phenomenon, “the industries take turns to perform,” in the domestic Taiwan stock market, we try to develop a trading strategy based on industry momentum. In line with the Momentum Life Cycle hypothesis introduced by Lee and Swaminathan (2000), we propose the “Early Momentum Strategy” (EMS) by going long past winners with low trading volume, and going short past losers with high trading volume in the same time. In comparison with the Early Momentum Strategy, we also construct the “Late Momentum Strategy” (LMS) by going long past winners with high trading volume and, simultaneously, going short past losers with low trading volume . Our empirical results tend to show that EMS is more profitable and reliable than Industry Momentum Strategy, while LMS is not.

    Contents 摘要.................................................................................................I Abstract.........................................................................................II 誌謝...............................................................................................III Contents.......................................................................................IV List of Tables..................................................................................V List of Figures...............................................................................VI Chapter 1. Introduction..................................................................1 1.1 Research Background................................................................1 1.2 Motivation and Purpose............................................................2 1.3 Research Process.....................................................................3 Chapter 2. Literature Review..........................................................4 2.1 Over Reaction...........................................................................4 2.2 Under Reaction.........................................................................6 2.3 Industry Momentum.................................................................7 2.4 Momentum Life Cycle Hypothesis............................................9 Chapter 3. Methodology...............................................................12 3.1 Data.........................................................................................12 3.2 Variable Definition...................................................................12 3.3 Portfolio Construction.............................................................14 Chapter 4. Empirical Results.........................................................17 4.1 Strategy Returns.....................................................................17 4.2 Single Side Analysis...............................................................20 4.3 The Improvement of EMS and LMS.........................................21 4.4 Robustness............................................................................22 Chapter 5. Conclusions and Suggestions.....................................24 References Appendix

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