Multivariate Data Analysis and Machine-Learning Models in Financial Analysis
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E5: Financial Mathematics".
Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 15327
Special Issue Editors
Interests: ESG principles; financial sustainability; sustainable business strategies; corporate governance
Special Issues, Collections and Topics in MDPI journals
Interests: business performance; financial modelling; statistics
Interests: financial performance; risk analysis; foreign direct investments; financial models; quantitative methods
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The complexity of financial decisions in an interconnected world has steadily increased in recent years and is accompanied by increased uncertainty driven by the pandemic and the unfolding of the post-pandemic realities. Thus, financial decision making, among other aspects, needs to consider multiple variables, measures and metrics and rely on advanced models for data comprehension and analysis. On the bright side, quantitative approaches in the field of multivariate data analysis and machine learning developed in recent decades have led the way towards improvements in addressing financial assessments and decisions. This Special Issue welcomes theoretical and empirical research papers that explore the multi-faceted financial analysis behind investing, financing and risk assessment and management in corporations and financial institutions alike, as well as providing an opportunity for scholars and the financial analysis industry to bring their insight and novel approaches to data analysis to light. Of particular interest are contributions on the concrete application of multivariate data analysis techniques and machine learning models to specific topics in financial analysis.
Prof. Dr. Stefania Cristina Curea
Prof. Dr. Lucian Belascu
Prof. Dr. Alexandra Horobet
Guest Editors
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Keywords
- financial analysis
- financial assessment
- financial decisions
- multivariate data analysis
- machine learning
- algorithms
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