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    題名: 高頻交易研究的演化及新興趨勢
    Evolution and emerging trends in HFT research
    作者: 李耀中
    Lee, Mike Y. J.
    貢獻者: 劉文卿
    Liu, Wenqing
    李耀中
    Lee, Mike Y. J.
    關鍵詞: High Frequency Trading
    HFT
    Social network analysis
    SNA
    emerging trends
    日期: 2019
    上傳時間: 2019-09-05 15:43:14 (UTC+8)
    摘要: In this research, the evolution and emerging trends of High Frequency Trading (HFT) research is conducted by examining papers published in the Web of Science (WOS) from 1993 to 2017. A total of 241 papers are included, and 1876 keywords from these articles were extracted and analyzed. For tracing the dynamic changes of the HFT Research, the whole 24 years are further separated into three consecutive periods: 1993-2002, 2003-2012, and 2013-2017. The Ucinet is adopted to get keywords network, or knowledge network, to study the relationship of each research theme. NetDraw is applied to visualize network. The social network analysis (SNA) technique is used to reveal patterns and trends in the research by measuring the association strength of terms representative of relevant publications produced in HFT field. Results indicate that HFT research has been strongly influenced by these keywords: “market”, “prices”, “finance”, “liquidity”, “statistics”, “financial markets”, “stock”, “stochastic”, “model” and “trades” as shown in Table 3, which represent some established research themes. These are major focuses and the bridges connecting to other research themes in HFT. The detailed analysis in “Discussions and implications” provides an overview of evolution and emerging trends in HFT Research. It concludes that “market performance” related keywords, which represent some established research themes, have become the major focus in HFT research. It also changes rapidly to embrace new themes. Especially, this research may make contribution to enlarge research method in that there is no SNA research in HFT research before.
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    描述: 博士
    國立政治大學
    資訊管理學系
    96356505
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0096356505
    資料類型: thesis
    DOI: 10.6814/NCCU201901120
    顯示於類別:[資訊管理學系] 學位論文

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