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系統識別號 U0026-1802201111190600
論文名稱(中文) 技術交易規則於全球期貨市場獲利性探討
論文名稱(英文) A Study of Profitability of Technical Trading Rules in Global Futures Markets
校院名稱 成功大學
系所名稱(中) 財務金融研究所
系所名稱(英) Graduate Institute of Finance & Banking
學年度 99
學期 1
出版年 100
研究生(中文) 黃婉玲
研究生(英文) Wan-Lin Haung
學號 r8797113
學位類別 碩士
語文別 中文
論文頁數 45頁
口試委員 口試委員-王澤世
口試委員-劉裕宏
指導教授-顏盟峯
中文關鍵字 技術分析  交易規則  拔靴真實性檢定  預測力優劣檢定法  資料探勘  定態拔靴 
英文關鍵字 technical analysis  trading rule  data snooping bias  BRC  SPA test  stationary bootstrap 
學科別分類
中文摘要 本文在探討技術分析在全球期貨市場之有效性,此議題一直被爭論著,為了檢定技術分析的有效性,本篇研究使用Hansen’s SPA test挑選20,970條交易規則應用到20個期貨市場,並將交易成本及保證金都考慮在內以跟現實狀況更為貼近。根據Marshall, Cahan, and Cahan (2008)的研究將檢定期間分為3個時期:全期、前期及後期,且分別檢定SPA左、右尾結果,觀察最佳交易規則是否能顯著擊敗無風險利率,及在此三期期中表現最差的交易規則。SPA test的結果顯示:在幾乎所有的期貨市場中,最好交易規則的表現皆能優於無風險利率,但在資料探勘誤差被調整後,這些好的績效能力就會消失,這結果和過去Marshall, Cahan, and Cahan (2008)的文獻結果一致。在全期中,僅於S&P500期貨市場找出一條績效顯著為正的交易規則,此結果可能是因為採用的交易規則數過多,因此,在前期及後期中改採STW所使用的7,846條交易規則來檢定,結果發現,前期中,於Euro FX、FT-100及TW期貨市場找出共三條績效顯著為正的交易規則;後期中,於Stoxx-50、FT-100及S&P500期貨市場找出共四條績效顯著為正的交易規則。在最差交易規則部分,交易規則運用在所有期貨市場都明顯劣於基準模型,在調整資料探勘問題後,幾乎期貨市仍明顯劣於基準模型。預測力優劣檢定的定態拔靴過程中,影響定態拔靴之區間大小的幾何分配之不同參數值會產生不同的p-value,造成一些分析上的影響,和之前的文獻相比,本篇研究同時採用四個參數值,因而能有更完整的考量。
英文摘要 This paper discusses Profitability of Technical Trading Rules in Global Futures It has been a disputation for a long time in the past.Based on Hansen’s SPA test (test for superior predictive ability), we examine the profitability of a universe of 20,970technical trading rules, which are selected from previous studies, in twenty twenty futures markets The transaction cost and the margin are taken into account for a practical manner. We also imitate the measure used by Marshall, Cahan, and Cahan (2008) for researching the whole interval and two equal sub-periods.We use SPA test with two-side to examine whether the best trading rule can significantly beat the benchmark of the risk-free rate in the full period, as well as in the first sub-period and the second sub-period. The results of the SPA show that the best trading rules are superior to the benchmark for almost all the futures markets; however, the outperformance vanishes after adjusting the data snooping bias, providing a consistency with the previous study of Marshall, Cahan, and Cahan (2008). The SPA test identifies only one statistically outperforming technical trading rule in the S&P 500 futures market during the full period. Containing numerous poor models (technical trading rules) may weaken its testing power, we adopt 7,846 technical trading rules used by STW to test the first sub-period and the second sub-period. During the first sub-period, three statistically outperforming ones are discovered in the Euro FX, FT-100 and TW futures markets. During the second sub-period, four statistically outperforming ones are found in the Stoxx-50, FT-100, and S&P 500 futures markets.
The results of the SPA show that the worst trading rules are inferior to the benchmark for all the futures markets; however, the underformance exists after adjusting the data snooping bias. The fours values of smooth parameter we conduct for the geometric distribution for the stationary bootstrap block size of the SPA test make p-value differ from each other, causing some influence for analysis. Adopting more values of this smooth parameter comparing to the previous works hence enable this paper more complete.
論文目次 目次
中文摘要 ............................................................ I
英文摘要 ........................................................... II
誌謝................................................................III
目次................................................................ IV
表目錄...............................................................VI
第一章 緒論 ..........................................................1
第一節 研究背景與動機...............................................1
第二節 研究目的.....................................................2
第三節 主要發現.....................................................3
第四節 貢獻.........................................................3
第五節 研究架構.....................................................4
第二章 文獻探討 ..................................................... 5
第三章 研究方法 ......................................................9
第一節 交易規則.....................................................9
第二節 預測力優劣檢定法 ...........................................11
第四章 資料 .........................................................15
第一節 資料來源 ...................................................15
第二節 報酬率計算 .................................................18
第五章 實證結果 .....................................................20
第六章 結論與未來研究建議 ...........................................39
第一節 結論 .........................................................39
第二節 未來研究建議 .................................................40
參考文獻 ............................................................44
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