This journal publishes research on the application of advanced data science techniques, including machine learning and neural networks, to financial problems such as portfolio optimization, risk management, option pricing, and market forecasting. Articles explore the use of these methods to analyze financial data, model interdependencies, and improve predictive accuracy in various markets, including equities, cryptocurrencies, and sovereign debt.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Publication & Citation Trend
Articles published
Times cited
2019
2020
2021
2022
2023
2024
2025
2026
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Applied MathematicsQ1
Business, Management and Accounting (miscellaneous)Q1
Statistics and ProbabilityQ1
Computer Science ApplicationsQ2
Economics and EconometricsQ2
FinanceQ2
Subject Classification
Web of Science Categories
Business, FinanceEconomics
Scopus Categories
Business, Management and Accounting (miscellaneous)FinanceApplied MathematicsComputer Science ApplicationsEconomics and EconometricsStatistics and Probability
Research Topics (OpenAlex)
Financial Markets and Investment StrategiesStock Market Forecasting MethodsMarket Dynamics and VolatilityFinancial Risk and Volatility ModelingComplex Systems and Time Series AnalysisEnergy Load and Power ForecastingCredit Risk and Financial RegulationsMonetary Policy and Economic ImpactStochastic processes and financial applicationsBanking stability, regulation, efficiency