Big data/machine learning
- Machine Learning Algorithms to Classify Future Returns Using Structured and Unstructured DataJoshua Livnat and Jyoti SinghThe Journal of Investing February 2021, joi.2021.1.169; DOI: https://doi.org/10.3905/joi.2021.1.169
- Hierarchical Clustering-Based Asset AllocationThomas RaffinotThe Journal of Portfolio Management December 2017, 44 (2) 89-99; DOI: https://doi.org/10.3905/jpm.2018.44.2.089
- Machine Learning for Structured FinanceEric KolchinskyThe Journal of Structured Finance October 2018, 24 (3) 7-25; DOI: https://doi.org/10.3905/jsf.2018.24.3.007
- Machine Learning for Algorithmic Trading and Trade Schedule OptimizationRobert Kissell and Jungsun “Sunny” BaeThe Journal of Trading October 2018, 13 (4) 138-147; DOI: https://doi.org/10.3905/jot.2018.13.4.138
- Improving Investment Operations through Data Science: A Case Study of Innovation in ValuationArthur Guimarães, Ashby Monk and Sidney PorterThe Journal of Portfolio Management October 2018, 45 (1) 125-140; DOI: https://doi.org/10.3905/jpm.2018.1.083
- Artificial Intelligence Update—Gaining Ground across Many SectorsJohn MathisThe Journal of Private Equity November 2018, 22 (1) 17-18; DOI: https://doi.org/10.3905/jpe.2018.22.1.017
- The 10 Reasons Most Machine Learning Funds FailMarcos López de PradoThe Journal of Portfolio Management June 2018, 44 (6) 120-133; DOI: https://doi.org/10.3905/jpm.2018.44.6.120
- Volatility Aversion in the Options Market Based on News SentimentMatthias W. UhlThe Journal of Derivatives May 2018, 25 (4) 24-35; DOI: https://doi.org/10.3905/jod.2018.25.4.024
- A Posteriori Multistage Optimal Trading under Transaction Costs and a Diversification ConstraintMogens Graf Plessen and Alberto BemporadThe Journal of Trading July 2018, 13 (3) 67-83; DOI: https://doi.org/10.3905/jot.2018.1.064
- Innovations are Coming to the Human ResourceJohn MathisThe Journal of Private Equity August 2018, 21 (4) 14-17; DOI: https://doi.org/10.3905/jpe.2018.21.4.014
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