臺灣博碩士論文加值系統

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.

1. Introduction 7
1.1 Background 7
1.1.1 What is High-Frequency Trading (HFT) 8
1.1.2 How does HFT work? 9
1.1.3 Basics of High-Frequency Trading 10
1.1.4 What’s the importance of speed in trading? 10
1.1.5 High Frequency Trading Strategies 11
1.1.5.1 Market making 12
1.1.5.2 Fraud 13
1.1.5.3 Ticker tape trading 13
1.1.5.4 Event arbitrage 14
1.1.5.5 Statistical arbitrage 14
1.1.5.6 Index arbitrage 15
1.1.5.7 News-based trading 15
1.1.5.8 Low-latency strategies 15
1.1.5.9 Order properties strategies 16
1.1.6 What algorithms are used in HFT? 16
1.1.7 Benefits and critiques of HFT 17
1.2 History of high-frequency trading 18
1.2.1 Market growth 20
1.2.2 Market share 20
1.3 Definition of high-frequency trading 22
1.3.1 Metrics for Defining HFT from SEC 22
1.3.2 HFT definition from NASDAQ.com 23
1.3.3 HFT definition from Wikipedia 23
1.3.4 HFT definition from Investopedia 23
1.3.5 Conclusion 24
1.4 Current qualitative research in HFT 24
1.5 Research categories and findings in HFT 25
1.6 Problems being investigated 29
1.7 General approach 30
1.8 Purpose of the Research 30
2. Literature review 32
2.1 Social network analysis (SNA) 32
2.2 Some SNA measures 32
2.2.1 SNA measure 1 : Degree Centrality 33
2.2.2 SNA measure 2 : Betweenness centrality 33
2.2.3 SNA measure 3 : Closeness centrality 34
2.2.4 SNA measure 4 : PageRank 35
2.2.5 SNA measure 5 : EigenCentrality 35
2.3 Some SNA software packages 36
2.3.1 KeyLines from Cambridge Intelligence 36
2.3.2 UCINET 6 for Windows 37
2.4 Bibliometrics 37
2.4.1 Bradford’s law 38
2.4.2 Lotka's law 38
2.4.3 Zipf's law 38
2.4.4 Comparison and Summary 39
2.4.5 Other Bibliometrics methods 39
2.4.5.1 Publication outputs of paper titles 39
2.4.5.2 Publication outputs of KeyWords Plus 40
2.4.5.3 Publication outputs by abstract analysis 40
3. Research methods 41
3.1 Purpose of the research 41
3.2 Materials and methods 41
3.2.1 Author keywords 42
3.2.2 Keywords Plus 43
3.2.3 Screening Methodology 43
3.3 Refinement of keywords and keywords databases 43
3.4 Constructing keywords network 44
3.5 Centrality measures of the SNA network 45
3.6 Network visualizations 45
4. The experiment and results 47
4.1 Keywords network 47
4.2 Betweenness centrality measuring for all period (1993-2017) 48
4.3 Changes in important keywords over time 50
5. Discussions and implications 52
5.1 The findings of the quantitative analysis results 52
5.2 Comparison with previous qualitative research in HFT
54
6. Conclusion 56
6.1 The original problem statement 56
6.2 Summarization 56
6.3 Limitations 57
6.4 Paths for future research 57
Reference 59

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