Structural analysis and evolutionary exploration based on the research topic network of a field: a case in high-frequency trading

Autores/as

DOI:

https://doi.org/10.3145/epi.2022.may.14

Palabras clave:

Research topic network, Evolutionary analysis, Scientometrics, NEViewer, Gephi, High-frequency trading, Emerging trends, Graphs

Resumen

This study aims to systematically analyze the distribution dynamics of research topics and uncover the development state of the research in the specific field, which will provide a practical reference for developing professional subject knowledge services in the era of big data. The research topic network is constructed and analyzed using methods and tools of scientometrics. Basic statistics on network characteristics are performed to reveal the research status. Community detection, node ordering, and other steps are conducted to generate the evolutionary alluvial diagram. Then, relevant results are analyzed to explore the knowledge structure of the specific field and evolutionary context of research topics. Visualization analysis on the network structure of the latest period is executed to distinguish related concepts and predict the research trends. Taking high-frequency trading (HFT) as a case, this study achieves diversified scientometrics analysis of the research topic network and multi-dimensional evolution exploration of the relevant research topics in the specific field, which obtaining some knowledge insights. (1) Six major topics in HFT: liquidity & market microstructure, market efficiency, financial market, incomplete market, cointegration & price discovery, and event study. (2) The research focus about markets gradually transferred from international to emerging, meanwhile continuous attention to volatility/risk related issues. (3) The emphasis will change from theory to practice, technologies (big data, etc.) and theories (behavioral finance, etc.) will have more interaction with HFT. An effective research idea is proposed to reveal the knowledge structure of field and analyze the evolutionary context of research topics, which demonstrating the knowledge insights.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Aldridge, Irene (2009). High-frequency trading: A practical guide to algorithmic strategies and trading systems. Hoboken: John Wiley & Sons, Inc. ISBN: 978 0 470 56376 2

Bastian, Mathieu; Heymann, Sebastien; Jacomy, Mathieu (2009). "Gephi: An open source software for exploring and manipulating networks". In: Proceedings of the International AAAI Conference on web and social media, pp. 361-362. https://doi.org/10.13140/2.1.1341.1520

Biais, Bruno; Foucault, Thierry; Moinas, Sophie (2015). "Equilibrium fast trading". Journal of financial economics, v. 116, n. 2, pp. 292-313. https://doi.org/10.1016/j.jfineco.2015.03.004

Budish, Eric; Cramton, Peter; Shim, John (2015). "The high-frequency trading arms race: Frequent batch auctions as a market design response". Quarterly journal of economics, v. 130, n. 4, pp. 1547-1621. https://doi.org/10.1093/qje/qjv027

Chou, Jerome-Chih-Lung; Lee, Mike Y. J.; Hung, Chia-Liang (2016). "Bibliometric analysis of emerging trends in high frequency trading research". In: Frontier computing, pp. 985-991. https://doi.org/10.1007/978-981-10-0539-8_96

Chung, Kee H.; Lee, Albert J. (2016). "High-frequency trading: Review of the literature and regulatory initiatives around the world". Asia-Pacific journal of financial studies, v. 45, n. 1, pp. 7-33. https://doi.org/10.1111/ajfs.12120

Currie, Wendy L.; Seddon, Jonathan J. M. (2016). "The regulatory, technology and market "dark arts trilogy" of high frequency trading: A research agenda". Journal of information technology, v. 32, n. 2, pp. 111-126. https://doi.org/10.1057/s41265-016-0025-3

Garcia, Patricia; Lueck, Joseph; Yakel, Elizabeth (2019). "The pedagogical promise of primary sources: Research trends, persistent gaps, and new directions". Journal of academic librarianship, v. 45, n. 2, pp. 94-101. https://doi.org/10.1016/j.acalib.2019.01.004

Goldstein, Michael A.; Kumar, Pavitra; Graves, Frank C. (2014). "Computerized and high-frequency trading". Financial review, v. 49, n. 2, pp. 177-202. https://doi.org/10.1111/fire.12031

Gomber, Peter; Arndt, Bjí¶rn; Lutat, Marco; Uhle, Tim (2011). "High-frequency trading". SSRN Electronic journal, pp. 1-86. https://doi.org/10.2139/ssrn.1858626

Gu, Dongxiao; Li, Tongtong; Wang, Xiaoyu; Yang, Xuejie; Yu, Zhangrui (2019). "Visualizing the intellectual structure and evolution of electronic health and telemedicine research". International journal of medical informatics, v. 130, 103947. https://doi.org/10.1016/j.ijmedinf.2019.08.007

Gu, Dongxiao; Yang, Xuejie; Deng, Shuyuan; Liang, Changyong; Wang, Xiaoyu; Wu, Jiao; Guo, Jingjing (2020). "Tracking knowledge evolution in cloud health care research: Knowledge map and common word analysis". Journal of medical internet research, v. 22, n. 2, e15142. https://doi.org/10.2196/15142

Guo, Huadong; Wang, Lizhe; Chen, Fang; Liang, Dong (2014). "Scientific big data and digital Earth". Chinese science bulletin, v. 59, n. 12, pp. 1047-1054. https://doi.org/CNKI:SUN:KXTB.0.2014-12-001

Hoffmann, Peter (2014). "A dynamic limit order market with fast and slow traders". Journal of financial economics, v. 113, n. 1, pp. 156-169. https://doi.org/10.1016/j.jfineco.2014.04.002

Howe, Doug; Costanzo, Maria; Fey, Petra; Gojobori, Takashi; Hannick, Linda; Hide, Winston; Hill, David P; Kania, Renate; Schaeffer, Mary; St Pierre, Susan; Twigger, Simon; White, Owen; Rhee, Seung Yon (2008). "Big data: The future of biocuration". Nature, v. 455, n. 7209, pp. 47-50. https://doi.org/10.1038/455047a

Huang, Han; Wang, Hongyu; Wang, Xiaoguang (2020). "An analysis framework of research frontiers based on the large-scale open academic graph". In: Proceedings of the Association for Information Science and Technology, v. 57, n. 1, e307. https://doi.org/10.1002/pra2.307

IBISWorld (2012). High frequency trading industry in the US - Market research report. https://www.ibisworld.com/industry-trends/specialized-market-research-reports/advisory-financial-services/intermediaries/high-frequency-trading.html

Lei, Lei; Deng, Yaochen; Liu, Dilin (2020). "Examining research topics with a dependency-based noun phrase extraction method: a case in accounting". Library hi tech, ahead-of-print. https://doi.org/10.1108/LHT-12-2019-0247

Li, Ping; Gong, Xuhong; Zhang, Qingchang (2011). "Diffusion of technical knowledge based on international citations: Evidence from China". Management world, v. 12, pp. 21-31. https://doi.org/10.19744/j.cnki.11-1235/f.2011.12.003

Linton, Oliver; Mahmoodzadeh, Soheil (2018). "Implications of high-frequency trading for security markets". Annual review of economics, v. 10, n. 1, pp. 237-259. https://doi.org/10.1146/annurev-economics-063016-104407

Moradi, Shima (2020). "The scientometrics of literature on smart cities". Library hi tech, v. 38, n. 2, SI, pp. 385-398. https://doi.org/10.1108/LHT-12-2018-0203

Moral-Muñoz, José A.; Herrera-Viedma, Enrique; Santisteban-Espejo, Antonio; Cobo, Manuel J. (2020). "Software tools for conducting bibliometric analysis in science: An up-to-date review". Profesional de la informacion, v. 29, n. 1, e290103. https://doi.org/10.3145/epi.2020.ene.03

O´Hara, Maureen (2015). "High frequency market microstructure". Journal of financial economics, v. 116, n. 2, pp. 257-270. https://doi.org/10.1016/j.jfineco.2015.01.003

Serenko, Alexander (2021). "A structured literature review of scientometric research of the knowledge management discipline: A 2021 update". Journal of knowledge management, v. 25, n. 8, pp. 1889-1925. https://doi.org/10.1108/JKM-09-2020-0730

Staff of the Division of Trading and Markets (2014). "Equity market structure literature review. Part II: High frequency trading". https://www.sec.gov/marketstructure/research/hft_lit_review_march_2014.pdf

Virgilio, Gianluca-Piero-Maria (2019). "High-frequency trading: A literature review". Financial markets and portfolio management, v. 33, n. 2, pp. 183-208. https://doi.org/10.1007/s11408-019-00331-6

Wang, Kang; Gao, Jiping; Pan, Yuntao; Chen, Yue (2021). "Research on the method of multi-position research themes recognition and evolution path". Library and information service, v. 65, n. 11, pp. 113-122. https://doi.org/10.13266/j.issn.0252-3116.2021.11.012

Wang, Xiaoguang; Cheng, Qikai (2013). "Analysis on evolution of research topics in a discipline based on NEViewer". Journal of the China Society for Scientific and Technical Information, v. 32, n. 9, pp. 900-911. https://doi.org/10.3772/j.issn.1000-0135.2013.09.001

Wang, Xiaoguang; Wang, Hongyu; Huang, Han (2021). "Evolutionary exploration and comparative analysis of the research topic networks in information disciplines". Scientometrics, v. 126, n. 6, pp. 4991-5017. https://doi.org/10.1007/s11192-021-03963-6

Yu, Dejian; Sheng, Libo (2020). "Knowledge diffusion paths of blockchain domain: The main path analysis". Scientometrics, v. 125, n. 1, pp. 471-497. https://doi.org/10.1007/s11192-020-03650-y

Zupko, Robert (2021). "Global algorithmic capital markets: High frequency trading, dark pools, and regulatory challenges [Book review]". The social science journal, Online first. https://doi.org/10.1080/03623319.2021.2015910

Publicado

2022-06-06

Cómo citar

Xia, M., Huang, H., Wang, H., & Lin, J. (2022). Structural analysis and evolutionary exploration based on the research topic network of a field: a case in high-frequency trading. Profesional De La información, 31(3). https://doi.org/10.3145/epi.2022.may.14

Número

Sección

Artí­culos de investigación / Research articles