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研究生:王婕瑜
研究生(外文):Chieh-Yu Wang
論文名稱:函數型資料分析在高頻匯率共整合配對交易之應用
論文名稱(外文):The Cointegration and Pairs Trading Strategy of High Frequency Foreign Exchange Rate with Functional Data Analysis
指導教授:陳美源陳美源引用關係
指導教授(外文):Mei-Yuan Chen
口試委員:蔡宗武李超雄丘政民
口試委員(外文):Zong-Wu CaiChao-Hsiung LeeJeng-Min Chiou
口試日期:2019-06-13
學位類別:碩士
校院名稱:國立中興大學
系所名稱:財務金融學系所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:62
中文關鍵詞:函數型資料分析高頻匯率資料動態避險模型
外文關鍵詞:Functional Data AnalysisHigh Frequency Foreign Exchange Rate DataDynamic Hedging Pairs Trading Model
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隨著影響國際市場的事件出現頻繁,進而影響了國際投資人的避險情緒,若單一投資於避險貨幣,如日圓,可能會承擔過多的匯率風險。因此,本論文試圖提出一動態避險配對交易模型,適時地調整操作策略,期許能到最佳的避險效益。

本論文以2018年日內匯率報價資料為研究樣本,分別將日圓、澳幣、加幣、瑞郎、歐元、英鎊及紐幣且資料頻率為一分鐘之歷史報價進行資料函數化,轉為平滑的函數型資料。基於函數型資料分析,本論文透過函數型單根檢定尋找變數成為穩定序列所需的差分階次後,接著以函數型單根檢定尋找日圓與其他具有相同差分階次的變數間是否具有共整合長期均衡關係。在變數間具有長期均衡關係下,以函數型向量誤差修正模型進行匯率預測。

本論文之動態避險配對交易模型,由具有長期均衡關係之匯率組成,以120個交易日做為配對形成期,下一個交易日做為交易期,並以預期價差長期會收斂至歷史均值的邏輯下進行策略操作。另外,為了優化交易權重,本論文導入預測技術於權重估計期中,進而達到更佳的績效。

經由本論文實證結果,高頻函數型資料日圓與澳幣、歐元及紐幣具有長期共整合關係,並且基於函數型資料分析下建構的動態避險配對交易模型,平均每次交易可獲得7.9%報酬率,且在納入預測技術之模型後,平均每次交易報酬率可達9%,以此確立納入預測技術後能帶來優化交易權重之效果,為本研究推薦投資人使用之模型。
摘要 i
Abstract ii
目次 iii
表目次 iv
圖目次 v
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機與目的 3
第三節 研究架構 3
第二章 文獻探討 5
第一節 價格均數回歸現象(Mean Reversion Phenomenon) 5
第二節 配對交易策略 6
第三節 配對交易於高頻資料研究 11
第四節 函數型資料分析 14
第三章 研究方法 16
第一節 函數型資料分析(Functional Data Analysis, FDA) 18
第二節 函數型單根檢定(Functional Unit Root Test) 26
第三節 函數型共整合檢定(Functional Cointegration Test)29
第四節 函數型向量誤差修正模型 38
第五節 動態配對交易避險模型 40
第四章 實證結果與討論 44
第一節 資料選取與樣本期間 44
第二節 函數型單根檢定 47
第三節 函數型共整合檢定 49
第四節 函數型匯率預測 53
第五節 配對交易實證結果 54
第五章 結論與建議 57
第一節 研究結論 57
第二節 研究建議 57
參考文獻 59
一、中文參考文獻
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張宗載 (2005),「一籃子貨幣避險」,國立台灣大學財務金融研究學所碩士論文。
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