Big data/machine learning
- The Buyside and the Three Phase-Evolution of Electronic TradingPeter CurleyThe Journal of Trading December 2006, 2 (1) 103-106; DOI: https://doi.org/10.3905/jot.2007.669807
- When Transactions Went High-TechNikolaj Hesselholt MunckThe Journal of Trading September 2006, 1 (4) 90-103; DOI: https://doi.org/10.3905/jot.2006.654305
- Accessing Displayed and Non-Displayed LiquidityKwaku Abrokwah and George SofianosThe Journal of Trading September 2006, 1 (4) 47-57; DOI: https://doi.org/10.3905/jot.2006.654301
- Using Neural Networks to Analyze Intermarket RelationshipsLouis B. MendelsohnThe Journal of Trading June 2006, 1 (3) 20-24; DOI: https://doi.org/10.3905/jot.2006.644085
- High-Frequency Trading: Implications for Markets,
Regulators, and EfficiencyJayaram Muthuswamy, John Palmer, Nivine Richie and Robert WebbThe Journal of Trading December 2010, 6 (1) 87-97; DOI: https://doi.org/10.3905/jot.2011.6.1.087 - Bringing Intelligent Decision-Making to Order RoutingDhiren RawalThe Journal of Trading December 2009, 5 (1) 30-34; DOI: https://doi.org/10.3905/JOT.2010.5.1.030
- The Value of LiquidityChris Sparrow and Denis IlijanicThe Journal of Trading December 2009, 5 (1) 10-15; DOI: https://doi.org/10.3905/JOT.2010.5.1.010
- Editor’s LetterBrian R BruceThe Journal of Trading December 2009, 5 (1) 1; DOI: https://doi.org/10.3905/JOT.2010.5.1.001
- Robo-Advisors Today and Tomorrow: Investment Advice Is Just an App AwayAdam Grealish and Petter N. KolmThe Journal of Wealth Management October 2021, 24 (3) 144-155; DOI: https://doi.org/10.3905/jwm.2021.1.149
- Big Data, Small Pickings: Predicting the Stock Market with Google TrendsWai Mun FongThe Journal of Index Investing February 2017, 7 (4) 75-82; DOI: https://doi.org/10.3905/jii.2017.7.4.075
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