博碩士論文 103428014 詳細資訊




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姓名 洪禎蔚(Zhen-Wei Hong)  查詢紙本館藏   畢業系所 財務金融學系
論文名稱 演算法交易對市場日內價格效率性的影響: 以外匯市場為例
(The Effect of Algorithmic Trading on Intraday Price Efficiency: Evidence from Foreign Exchange Market)
檔案 [Endnote RIS 格式]    [Bibtex 格式]    至系統瀏覽論文 (2020-6-30以後開放)
摘要(中) 本論文研究演算法交易(algorithmic trading)對外匯市場價格效率性的影響,採用歐元兌美元及日圓兌美元的日內交易報價資料,建構結構性向量自我迴歸(SVAR)模型進行分析,發現演算法交易與市場交易規模呈現相反的趨勢線圖,且演算法交易與市場價格效率性呈現反向關係,即演算法交易傾向在市場效率性較差時進入市場,最後,發現當演算法交易愈活絡時,市場效率性會隨之提升,說明演算法交易能夠改善市場效率,且可進一步推測演算法交易者為資訊交易者(informed traders)。
摘要(英) This thesis studies the impact of algorithmic trading (AT) on informational efficiency in the foreign exchange market. My data rely on a novel of intraday data consisting of both quote data and transaction data in two currency pairs: euro-dollar, and dollar-yen. The thesis estimates a structural vector autoregression model. The results show that AT exhibits a strong reverse pattern with trade size, and that greater AT activity is related to lower market efficiency which suggests that algorithmic traders strategically enter the market when informational efficiency is lower. AT is associated with an increase in market efficiency in the subsequent intraday period. The results strongly suggest that algorithmic trading is helpful for market efficiency and algorithmic traders are informed.
關鍵字(中) ★ 演算法交易
★ 外匯市場
★ 市場價格效率性
★ 日內資料
關鍵字(英) ★ algorithmic trading
★ foreign exchange market
★ market efficiency
★ intraday data
論文目次 目錄
摘要 i
Abstract ii
致謝 iii
表目錄 vi
圖目錄 vi
第一章、緒論 1
第一節、研究背景 1
第二節、研究動機 2
第三節、研究目的 4
第四節、本文架構 5
第二章、文獻回顧 6
第一節、演算法交易者的行為特性 6
第二節、文獻上如何定義市場演算法交易者 7
第三節、衡量市場價格效率性的實證模型 8
第四節、演算法交易對市場的正面效果 9
第五節、演算法交易對市場的負面效果 11
第六節、研究假說 12
第三章、研究樣本 13
第一節、外匯市場的概述 13
第二節、資料來源與處理 13
第四章、研究方法 15
第一節、演算法交易的替代變數 15
第二節、市場價格效率性的衡量方式 15
第三節、模型設定 18
第五章、實證結果 20
第一節、敘述性統計 20
第二節、演算法交易與訂價錯誤的日內型態 20
第三節、實證迴歸結果 21
第六章、結論與建議 24
參考文獻 25
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指導教授 高櫻芬(Yin-Feng Gau) 審核日期 2016-7-5
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