Big data/machine learning
- Industry Return Predictability: A Machine Learning ApproachDavid E. Rapach, Jack K. Strauss, Jun Tu and Guofu ZhouThe Journal of Financial Data Science July 2019, 1 (3) 9-28; DOI: https://doi.org/10.3905/jfds.2019.1.3.009
- The ETS Challenges: A Machine Learning Approach to the Evaluation of Simulated Financial Time Series for Improving Generation ProcessesJavier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Maria Planas, Jorge Cubero, Rafael Cobo and Fernando PablosThe Journal of Financial Data Science July 2019, 1 (3) 68-86; DOI: https://doi.org/10.3905/jfds.2019.1.3.068
- Default Prediction of Commercial Real Estate Properties Using Machine Learning TechniquesChad Cowden, Frank J. Fabozzi and Abdolreza NazemiThe Journal of Portfolio Management September 2019, 45 (7) 55-67; DOI: https://doi.org/10.3905/jpm.2019.1.104
- AI and Machine Learning in Real Estate InvestmentJennifer Conway ViriatoThe Journal of Portfolio Management September 2019, 45 (7) 43-54; DOI: https://doi.org/10.3905/jpm.2019.45.7.043
- Cross-Predictability of Industry Return in Trade Network: Using LASSORasha AshrafThe Journal of Investing September 2019, 28 (6) 42-54; DOI: https://doi.org/10.3905/joi.2019.1.095
- A Backtesting Protocol in the Era of Machine LearningRob Arnott, Campbell R. Harvey and Harry MarkowitzThe Journal of Financial Data Science January 2019, 1 (1) 64-74; DOI: https://doi.org/10.3905/jfds.2019.1.064
- Big Data in Portfolio Allocation: A New Approach to Successful Portfolio OptimizationIrene AldridgeThe Journal of Financial Data Science January 2019, 1 (1) 45-63; DOI: https://doi.org/10.3905/jfds.2019.1.045
- A Machine Learning Approach to Risk Factors: A Case Study Using the Fama–French–Carhart ModelJoseph Simonian, Chenwei Wu, Daniel Itano and Vyshaal NarayanamThe Journal of Financial Data Science January 2019, 1 (1) 32-44; DOI: https://doi.org/10.3905/jfds.2019.1.032
- Triumph of the Empiricists: The Birth of Financial Data ScienceJoseph Simonian and Frank J. FabozziThe Journal of Financial Data Science January 2019, 1 (1) 10-13; DOI: https://doi.org/10.3905/jfds.2019.1.010
- Modeling Analysts’ Recommendations via Bayesian Machine LearningDavid Bew, Campbell R. Harvey, Anthony Ledford, Sam Radnor and Andrew SinclairThe Journal of Financial Data Science January 2019, 1 (1) 75-98; DOI: https://doi.org/10.3905/jfds.2019.1.1.075
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