IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v209y2024ics0040162524005444.html
   My bibliography  Save this article

Technology-driven advancements: Mapping the landscape of algorithmic trading literature

Author

Listed:
  • Horobet, Alexandra
  • Boubaker, Sabri
  • Belascu, Lucian
  • Negreanu, Cristina Carmencita
  • Dinca, Zeno

Abstract

Our study is a comprehensive examination of the existing literature pertaining to algorithmic trading and its temporal progression in a framework driven by technology development. A total of 4552 papers were analyzed, spanning the period from 1990 to 2023. Performance metrics evaluation and science mapping approaches were utilized in this study. The data was obtained from the Scopus database, and the analysis was conducted using the Biblioshiny environment. The research landscape has undergone significant changes in recent years due to advancements in data-driven technology and the implementation of sophisticated algorithms such as machine learning, deep learning, and genetic algorithms. The shift in research interest has been particularly pronounced in the last decade compared to earlier periods. The most significant contribution in terms of production is associated with authors who are affiliated with the People's Republic of China. Another significant discovery is the limited knowledge dissemination and collaboration among scholars, as seen by the examination of co-authorship in academic papers. In relation to the conceptual framework of the study domain, we have identified two primary trajectories, specifically financial markets, and energy markets, whereby the utilization of deep learning techniques has garnered significant attention.

Suggested Citation

  • Horobet, Alexandra & Boubaker, Sabri & Belascu, Lucian & Negreanu, Cristina Carmencita & Dinca, Zeno, 2024. "Technology-driven advancements: Mapping the landscape of algorithmic trading literature," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524005444
    DOI: 10.1016/j.techfore.2024.123746
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162524005444
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2024.123746?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Wang, Yongli & Wang, Yudong & Huang, Yujing & Yang, Jiale & Ma, Yuze & Yu, Haiyang & Zeng, Ming & Zhang, Fuwei & Zhang, Yanfu, 2019. "Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Bhanu Sharma & Ruppa K. Thulasiram & Parimala Thulasiraman, 2015. "Computing value-at-risk using genetic algorithm," Journal of Risk Finance, Emerald Group Publishing, vol. 16(2), pages 170-189, March.
    5. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    6. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    7. Rahul Ravi & Youna Hong, 2015. "Information asymmetry around S&P 500 index changes," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 14(2), pages 106-127, May.
    8. Luca Arciero & Ronald Heijmans & Richard Heuver & Marco Massarenti & Cristina Picillo & Francesco Vacirca, 2014. "How to measure the unsecured money market? The Eurosystem�s implementation and validation using TARGET2 data," Questioni di Economia e Finanza (Occasional Papers) 215, Bank of Italy, Economic Research and International Relations Area.
    9. Ahmet Murat Ozbayoglu & Mehmet Ugur Gudelek & Omer Berat Sezer, 2020. "Deep Learning for Financial Applications : A Survey," Papers 2002.05786, arXiv.org.
    10. Ping Liu & Zexiang Cai & Peng Xie & Xiaohua Li & Yongjun Zhang, 2019. "A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process," Energies, MDPI, vol. 12(8), pages 1-19, April.
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    13. Sihem Khemakhem & Younes Boujelbene, 2018. "Predicting credit risk on the basis of financial and non-financial variables and data mining," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 17(3), pages 316-340, August.
    14. M.J. Cobo & A.G. López‐Herrera & E. Herrera‐Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    15. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    16. Kurz, W.A. & Dymond, C.C. & White, T.M. & Stinson, G. & Shaw, C.H. & Rampley, G.J. & Smyth, C. & Simpson, B.N. & Neilson, E.T. & Trofymow, J.A. & Metsaranta, J. & Apps, M.J., 2009. "CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards," Ecological Modelling, Elsevier, vol. 220(4), pages 480-504.
    17. Rahul Ravi & Youna Hong, 2015. "Information asymmetry around S&P 500 index changes," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 14(2), pages 106-127, May.
    18. Katherine W. McCain, 1990. "Mapping authors in intellectual space: A technical overview," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 433-443, September.
    19. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1469-1497, August.
    20. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    21. Rahul Ravi & Youna Hong, 2015. "Information asymmetry around S&P 500 index changes," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 14(2), pages 106-127, May.
    22. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    23. Domowitz, Ian, 1990. "The mechanics of automated trade execution systems," Journal of Financial Intermediation, Elsevier, vol. 1(2), pages 167-194, June.
    24. Amir Mosavi & Pedram Ghamisi & Yaser Faghan & Puhong Duan, 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," Papers 2004.01509, arXiv.org.
    25. van Leeuwen, Gijs & AlSkaif, Tarek & Gibescu, Madeleine & van Sark, Wilfried, 2020. "An integrated blockchain-based energy management platform with bilateral trading for microgrid communities," Applied Energy, Elsevier, vol. 263(C).
    26. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    27. Frederik Kunze & Tobias Basse & Miguel Rodriguez Gonzalez & Günter Vornholz, 2020. "Forward-looking financial risk management and the housing market in the United Kingdom: is there a role for sentiment indicators?," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 21(5), pages 659-678, September.
    28. Hussain, Syed Mujahid & Ahmad, Nisar & Ahmed, Sheraz, 2023. "Applications of high-frequency data in finance: A bibliometric literature review," International Review of Financial Analysis, Elsevier, vol. 89(C).
    29. Sihem Khemakhem & Younes Boujelbene, 2018. "Predicting credit risk on the basis of financial and non-financial variables and data mining," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 17(3), pages 316-340, August.
    30. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    31. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    32. Christian L. Dunis & Jason Laws & Peter W. Middleton & Andreas Karathanasopoulos, 2013. "Nonlinear Forecasting Of The Gold Miner Spread: An Application Of Correlation Filters," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 207-231, October.
    33. Thomas A. Hanson, 2016. "High frequency traders in a simulated market," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 15(3), pages 329-351, August.
    34. Bekiros, Stelios & Loukeris, Nikolaos & Eleftheriadis, Iordanis, 2017. "Portfolio Optimization With Investor Utility Preference of Higher-Order Moments: A Behavioral Approach," Review of Behavioral Economics, now publishers, vol. 4(2), pages 83-106, September.
    35. Sun, Wei & Zhang, Chongchong, 2018. "Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm," Applied Energy, Elsevier, vol. 231(C), pages 1354-1371.
    36. Henry Small, 1999. "Visualizing science by citation mapping," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(9), pages 799-813.
    37. Bhanu Sharma & Ruppa K. Thulasiram & Parimala Thulasiraman, 2015. "Computing value-at-risk using genetic algorithm," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 16(2), pages 170-189, March.
    38. María Paula Lechuga Sancho & Alicia Martín-Navarro & Antonio Rafael Ramos-Rodríguez, 2020. "Information Systems Management Tools: An Application of Bibliometrics to CSR in the Tourism Sector," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    39. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    40. Rodrigo Costas & María Bordons, 2008. "Is g-index better than h-index? An exploratory study at the individual level," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(2), pages 267-288, November.
    41. M. C. Campi & S. Garatti, 2011. "A Sampling-and-Discarding Approach to Chance-Constrained Optimization: Feasibility and Optimality," Journal of Optimization Theory and Applications, Springer, vol. 148(2), pages 257-280, February.
    42. Xiao Zhong & David Enke, 2019. "Predicting the daily return direction of the stock market using hybrid machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    43. Mosavi, Amir & Faghan, Yaser & Ghamisi, Pedram & Duan, Puhong & Ardabili, Sina Faizollahzadeh & Hassan, Salwana & Band, Shahab S., 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," OSF Preprints jrc58, Center for Open Science.
    44. Howard D. White & Belver C. Griffith, 1981. "Author cocitation: A literature measure of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 32(3), pages 163-171, May.
    45. Amirhosein Mosavi & Yaser Faghan & Pedram Ghamisi & Puhong Duan & Sina Faizollahzadeh Ardabili & Ely Salwana & Shahab S. Band, 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," Mathematics, MDPI, vol. 8(10), pages 1-42, September.
    46. Howard D. White & Katherine W. McCain, 1998. "Visualizing a discipline: An author co‐citation analysis of information science, 1972–1995," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(4), pages 327-355.
    47. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pinho, Celso R.A. & Pinho, Maria Luiza C.A. & Deligonul, Seyda Z. & Tamer Cavusgil, S., 2022. "The agility construct in the literature: Conceptualization and bibliometric assessment," Journal of Business Research, Elsevier, vol. 153(C), pages 517-532.
    2. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    3. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    4. Carlos Sánchez‐Camacho & Rocío Carranza & David Martín‐Consuegra & Estrella Díaz, 2022. "Evolution, trends and future research lines in corporate social responsibility and tourism: A bibliometric analysis and science mapping," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(3), pages 462-476, June.
    5. Davidescu, Adriana AnaMaria & Petcu, Monica Aureliana & Curea, Stefania Cristina & Manta, Eduard Mihai, 2022. "Two faces of the same coin: Exploring the multilateral perspective of informality in relation to Sustainable Development Goals based on bibliometric analysis," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 683-705.
    6. Koseoglu, Mehmet Ali & Rahimi, Roya & Okumus, Fevzi & Liu, Jingyan, 2016. "Bibliometric studies in tourism," Annals of Tourism Research, Elsevier, vol. 61(C), pages 180-198.
    7. Enrico Ciavolino & Massimo Aria & Jun-Hwa Cheah & José Luis Roldán, 2022. "A tale of PLS Structural Equation Modelling: Episode I— A Bibliometrix Citation Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1323-1348, December.
    8. Tufan Özsoy & Konuralp Sezgili, 2024. "Exploring the Current Practices and Future Directions in Project Management Education and Training," SAGE Open, , vol. 14(1), pages 21582440241, March.
    9. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    10. Pedro López-Rubio & Norat Roig-Tierno & Alicia Mas-Tur, 2020. "Regional innovation system research trends: toward knowledge management and entrepreneurial ecosystems," International Journal of Quality Innovation, Springer, vol. 6(1), pages 1-16, December.
    11. Rakshith Bhandary & Sandeep S. Shenoy & Ankitha Shetty & Adithya D. Shetty, 2024. "Education loan repayment: a systematic literature review," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(4), pages 1365-1376, December.
    12. Zainuddin, Mohammad & Mahi, Masnun Al & Hassan, M. Kabir & Khan, Shamim Ahmed, 2024. "Platform economy deconstructed: intellectual bases and emerging ethical issues," Research in International Business and Finance, Elsevier, vol. 71(C).
    13. Baker, H. Kent & Kumar, Satish & Goyal, Kirti & Sharma, Anuj, 2021. "International review of financial analysis: A retrospective evaluation between 1992 and 2020," International Review of Financial Analysis, Elsevier, vol. 78(C).
    14. Wenceslao Arroyo-Machado & Daniel Torres-Salinas & Nicolas Robinson-Garcia, 2021. "Identifying and characterizing social media communities: a socio-semantic network approach to altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9267-9289, November.
    15. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    16. Dzikowski, Piotr, 2018. "A bibliometric analysis of born global firms," Journal of Business Research, Elsevier, vol. 85(C), pages 281-294.
    17. Shi, Xianwei & Liang, Xingkun & Luo, Yining, 2023. "Unpacking the intellectual structure of ecosystem research in innovation studies," Research Policy, Elsevier, vol. 52(6).
    18. Martha Flores-Sosa & José M. Merigó & Kenia Sanchez-Valenzuela, 2025. "30 years of the Journal of Heuristics: a bibliometric analysis," Journal of Heuristics, Springer, vol. 31(1), pages 1-55, March.
    19. Shashi & Piera Centobelli & Roberto Cerchione & Amit Mittal, 2021. "Managing sustainability in luxury industry to pursue circular economy strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 432-462, January.
    20. Centobelli, Piera & Cerchione, Roberto & Esposito, Emilio & Oropallo, Eugenio, 2021. "Surfing blockchain wave, or drowning? Shaping the future of distributed ledgers and decentralized technologies," Technological Forecasting and Social Change, Elsevier, vol. 165(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524005444. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.