Genetic algorithms and Darwinian approaches in financial applications: A survey

By Rubén Aguilar-Rivera, Manuel Valenzuela-Rendón, J. Rodríguez-Ortiz. 2015

146 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): “Later, Multiobjective Evolutionary Algorithms (MOEAs) were extensively surveyed on various financial applications including financial time series prediction [11, 12, 13].”
Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks (2019, methodology): “Besides these approaches, evolutionary and genetic algorithms are used to forecast stock market prices and index in literature [1].”
Applications of deep learning in stock market prediction: recent progress (2020, methodology): “Aguilar-Rivera et al. (2015) presents a review of the application of evolutionary computation methods to solving financial problems, including the techniques of genetic algorithms, genetic programming, multi-objective evolutionary algorithms, learning classifier systems, co-evolutionary approaches,…”
Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey (2018, methodology): “Financial application (Aguilar-Rivera et al. 2015), power systemoptimization (Akachukwu et al.”