Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review

By Yong Hu, Kang Liu, Xiangzhou Zhang, Lijun Su, Eric Wai Ting Ngai, Mei Liu. 2015

175 citations recorded by the source corpus.

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Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “[34] focused on EC implementations for stock forecasting and algorithmic trading models.”
News-based trading strategies (2016, background): “These test numerous variables and combinations thereof to identify predictors that might show a correlation with future stock returns [45].”
CNNpred: CNN-based stock market prediction using a diverse set of variables (2019, methodology): “…analysis, logistic regression and evolutionary computing algorithms, especially genetic algorithm (GA), (Hu et al., 2015b; Brown et al., 2013; Hu et al., 2015a; Atsalakis & Valavanis, 2009) are among other tools and techniques25 that have been applied for feature extraction from raw…”
AI in Finance: Challenges, Techniques, and Opportunities (2021, methodology): “Further, computational intelligence techniques and methods inspired by nature and human systems and simulating natural and human intelligence are used to model, characterize, and optimize EcoFin mechanisms, strategies, and systems, and to manage and optimize portfolio and market forecasting, and so ”