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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91210
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor洪志清zh_TW
dc.contributor.advisorChih-Ching Hungen
dc.contributor.author陳柏言zh_TW
dc.contributor.authorPo-Yen Chenen
dc.date.accessioned2023-12-12T16:13:40Z-
dc.date.available2023-12-13-
dc.date.copyright2023-12-12-
dc.date.issued2023-
dc.date.submitted2023-11-23-
dc.identifier.citationBarber, B. M., Y. T. Lee, Y. J. Liu, and T. Odean. (2007). Is the Aggregate Investor Reluctant to Realise Losses? Evidence from Taiwan. European Financial Management 13, 423–447.
Barber, B. M., Y. T. Lee, Y. J. Liu, T. Odean, and K. Zhang. (2020). Learning, Fast or Slow. Review of Asset Pricing Studies 10, 61–93.
Bessembinder, H., and K. Chan. (1998). Market Efficiency and the Returns to Technical Analysis. Financial Management 27, 5–17
Bhattacharya, U., W. Y. Kuo, T. C. Lin, and J. Zhao. (2018). Do Superstitious Traders Lose Money? Management Science 64, 3772–3791.
Blume, L., D. Easley, and M. O’Hara. (1994). “Market Statistics and Technical Analysis: The Role of Volume.” Journal of Finance 49, 153–181.
Brock, W., J. Lakonishok, and B. LeBaron (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance 47, 1731–1764.
Fama, E. F. and M. E. Blume. (1966). Filter Rules and Stock-Market Trading. Journal of Business 39, 226–241.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance 25, 383–417.
Gao, X., and T. C. Lin. (2015). Do Individual Investors Treat Trading as a Fun and Exciting Gambling Activity? Evidence from Repeated Natural Experiments. Review of Financial Studies 28, 2128–2166.
George, T. J., and C. Y. Hwang. (2004). The 52‐week high and momentum investing. Journal of Finance 59, 2145–2176.
Hsu, P. H., and C. M. Kuan. (2005). Reexamining the Profitability of Technical Analysis with Data Snooping Checks. Journal of Financial Econometrics 3, 606–628.
Hsu, P. H., Y. C. Hsu, and C. M. Kuan. (2010). Testing the Predictive Ability of Technical Analysis Using a New Stepwise Test without Data Snooping Bias. Journal of Empirical Finance 17, 471–484.
Lo, A. W., H. Mamaysky, and J. Wang. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. Journal of Finance 55, 1705–1765.
Sullivan, R., A. Timmermann, and H. White. (1999). Data‐snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance 54, 1647–1691.
White, H. (2000). A Reality Check for Data Snooping. Econometrica 68, 1097–1126.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91210-
dc.description.abstract本文以White(2000)一文提出的White真實性檢定(White’s Reality Check),在排除資料窺探偏誤的情況下,檢查技術交易策略在臺灣股票市場個股的獲利能力。這些策略由臺灣股市投資人熟悉之技術指標組合而成。本文發現部分進出場的技術交易策略,例如KD指標與MA指標之組合,確實能使特定個股在樣本期間內擊敗買進持有策略,獲取良好的報酬。本文將這些表現優異的技術交易策略進行樣本外之測試、並將交易成本納入考量,發現部分的技術交易策略,例如KD、MA與RSI指標之組合,之績效依然超越買進持有策略之績效。zh_TW
dc.description.abstractUsing White's Reality Check introduced in White (2000) to minimize data snooping bias, this paper examines the profitability of technical trading strategies in individual stocks in Taiwanese stock market. These strategies are composed of technical indicators. It turns out that certain technical trading strategies, e.g. combination of KD and MA indicators, indeed outperforms the buy-and-hold strategy for specific stocks during the sample period. Subsequently, this paper focuses on these high-performing technical trading strategies and performs out-of-sample tests while considering transaction costs. Some of these strategies, e.g. combination of KD, MA, and RSI indicators, continue to outperform the buy-and-hold strategy in terms of return.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-12-12T16:13:40Z
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dc.description.provenanceMade available in DSpace on 2023-12-12T16:13:40Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents摘要 I
ABSTRACT(英文摘要) II
目錄 III
表目錄 IV
第一章 前言 1
第二章 White真實性檢定 5
第三章 技術交易策略之建構 8
第一節 技術指標 8
第二節 交叉策略 13
第三節 結合「濾網」的交叉策略 13
第四章 實證結果 15
第一節 模擬一:臺灣50指數與臺灣高股息指數之成分股 15
第二節 模擬二:臺灣中型100之成分股 16
第三節 技術交易策略是否能擊敗買進持有策略? 17
第五章 結論 22
第六章 參考文獻 24
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dc.language.isozh_TW-
dc.subjectWhite 真實性檢定zh_TW
dc.subject交易策略zh_TW
dc.subject技術分析zh_TW
dc.subject資料窺探zh_TW
dc.subject交易策略zh_TW
dc.subject技術分析zh_TW
dc.subject資料窺探zh_TW
dc.subjectWhite 真實性檢定zh_TW
dc.subjectData-snoopingen
dc.subjectWhite’s reality checken
dc.subjectTechnical analysisen
dc.subjectTrading strategyen
dc.subjectWhite’s reality checken
dc.subjectData-snoopingen
dc.subjectTechnical analysisen
dc.subjectTrading strategyen
dc.title真實性檢定在技術分析議題上之應用:以台股市場為例zh_TW
dc.titleApplication of White’s Reality Check on Technical Analysis: Using Taiwanese Stock Market as Exampleen
dc.typeThesis-
dc.date.schoolyear112-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee王之彥;蕭湛東zh_TW
dc.contributor.oralexamcommitteeJr-Yan Wang;Chan-Tung Hsiaoen
dc.subject.keyword交易策略,技術分析,資料窺探,White 真實性檢定,zh_TW
dc.subject.keywordTrading strategy,Technical analysis,Data-snooping,White’s reality check,en
dc.relation.page25-
dc.identifier.doi10.6342/NTU202304438-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2023-11-24-
dc.contributor.author-college管理學院-
dc.contributor.author-dept財務金融學系-
顯示於系所單位:財務金融學系

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