系統識別號 U0026-0107201116513900
論文名稱(中文) 以無資料窺視偏誤檢定評估日間與日內技術交易法則於台股指數期貨之績效
論文名稱(英文) Examining the Performance of Daily and Intraday Technical Trading Rules in TAIEX Futures Market without Data-Snooping Bias
校院名稱 成功大學
系所名稱(中) 高階管理碩士在職專班(EMBA)
系所名稱(英) Executive Master of Business Administration (EMBA)
學年度 99
學期 2
出版年 100
研究生(中文) 楊淳和
研究生(英文) Tsun-Ho Yang
學號 r0796138
學位類別 碩士
語文別 中文
論文頁數 76頁
口試委員 指導教授-陳俊男
中文關鍵字 技術交易法則  資料窺視偏誤  靴環真實性檢定  預測力優劣檢定 
英文關鍵字 Technical Trading Rules  Data-snooping Bias  Bootstrap Reality Check  Test for Superior Predictive Ability 
中文摘要 為解決以過去歷史資料發掘最佳技術交易法則時,所可能產生資料窺視偏誤的問題,本研究參考White (2000)與Hansen (2005)分別所提出之靴環真實性檢定(White’s Bootstrap Reality Check),與預測力優劣檢定(Hansen’s Test for Superior Predictive Ability)等靴環重抽法,嘗試檢驗技術交易法則運用於台灣證券交易所股價指數期貨的績效。研究中檢驗五大類型之日內與日間技術交易法則,包括濾網法則、移動平均線法則、支撐與壓力法則、通道突破法則,日內動能投資策略等,與4580組、21230組不同範圍技術交易法則數,並考慮交易成本與交易時間點合理性等,以符合現實操作狀況。研究範圍期間自2001年1月2日至2008年12月31日止,檢定於樣本內期間,在考慮資料窺視偏誤條件下,是否存在最佳技術交易法則能擊敗基準模型。結果發現不論4580組或21230組法則數組合,當採用預測力優劣檢定,最佳技術交易法則能顯著擊敗基準模型。而採用靴環真實性檢定時,則會發生最佳技術法則的p-value過大無法得到擊敗基準模型的結論,情況符合Hansen (2005)對於靴環真實性檢定的批評。另外,進行定態靴環重抽法時,機率參數、靴環重抽次數與交易成本的不同,亦有可能會產生不同p-value。實證中亦另取不同機率參數、靴環重抽次數與交易成本等進行敏感度分析,確認所得結果的穩健性。最後檢視發現最佳法則於樣本外期間依然能得到正報酬績效。
英文摘要 In order to correct the problem of data-snooping bias that usually occurs when developing the best technical trading rules by using the historical financial data, this study utilizes two different bootstrap replication methods, including White’s Bootstrap Reality Check (White, 2000), and Hansen’s Test for Superior Predictive Ability (Hansen, 2005), to investigate the performance of daily and intraday technical trading rules in TAIEX futures market without data-snooping bias. The technical trading rules being examined include Filter Rules, Moving Averages Rules, Support and Resistance Rules, Channel Break-Outs Rules, and Intraday Momentum Investment Strategy, totally 4580 and 21230 trading rules which represent two different universes respectively. The transaction cost and rationality of transaction timing are also taken into account for a practical manner. The result shows that during the in-sample period, we can find the best trading rules generates statistically significant economic profits over the benchmark model by applying Hansen’s SPA test which corrects for data-snooping bias. But when applying White’s Reality Check, survey shows that it generates larger p-value then Hansen’s SPA test does, which conforms to the criticism made by Hansen (2005). This study also examines different values of smooth parameters, number of resamples and transaction costs, in order to review the robustness of the result. In the end, we find the best trading rule also exhibit positive return during out-of-sample period.
論文目次 目錄
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究架構 4
第二章 文獻探討 6
第一節 非隨機價格行為與價格可預測性 6
第二節 技術交易法則相關發展與運用 11
第三節 資料窺視偏誤解決方法 15
第三章 研究方法 19
第一節 解決資料窺視偏誤的檢定方法 19
第二節 技術交易法則與基準模型 24
第三節 資料來源與處理 40
第四節 報酬率計算與交易成本 42
第四章 實證結果 45
第一節 樣本內期間技術交易法則績效 45
第二節 不同機率參數q對檢定結果之影響 50
第三節 不同靴環重抽次數對檢定結果之影響 52
第四節 不同交易成本設定對檢定結果之影響 55
第五節 最佳技術法則於樣本外期間之績效 57
第五章 結論與建議 60
第一節 結論 60
第二節 建議 63
參考文獻 64
附錄 68
參考文獻 參考文獻

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