Short-term prediction of the Romanian stock market benchmark index using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.9154

@Article{Duma:2026:DF,

• author = "Florin-Sebastian Duma and Rodica-Ioana Lung",
• title = "Short-term prediction of the Romanian stock market benchmark index using genetic programming",
• journal = "Digital Finance: Smart Data Analytics, Investment Innovation, and Financial Technology",
• year = "2026",
• volume = "8",
• pages = "article number 21",
• keywords = "genetic algorithms, genetic programming, Stock market indices, Regression, Prediction, Bucharest Exchange Trading, GPLEARN, GPTIPS, M3GP, Fast Function Extraction, FFX, decision tree (DTR), random forests (RF), elastic net (EN), and linear regression (LR)",
• ISSN = "2524-6984",
• URL = "https://rdcu.be/pELon9fkQGma",
• DOI = "10.1007/s42521-026-00188-1",
• data_url = "https://datasetcatalog.nlm.nih.gov/dataset?q=0002924229",
• size = "24 pages",
• abstract = "... we offer an analysis of the connections between the Romanian stock market index BET and major indices from the USA (NASDAQ, S&P500, DIJA), Western Europe (FTSE100, CAC40, DAX), and Central and Eastern Europe (ATX, BUX, WIG20). The analysis explores the use of genetic programming tools to model BET index values using short-term intervals and compares them with standard machine learning models. Our findings indicate that short-term analysis presents significant challenges to all models...",
• notes = "Center for the Study of Complexity, Babes-Bolyai University, Cluj-Napoca, Romania",

}

Genetic Programming entries for Florin-Sebastian Duma Rodica-Ioana Lung

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