Vol. 5 No. 1 (2025): Issue 5
Articles

Logistic Regression-based method for Financial Risk Assessment

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  • Hans Müller,
  • Clara Schmidt,
  • Felix Weber,
  • Haibo Wang
Hans Müller
Institute of Data Science and Artificial Intelligence, Leipzig University of Applied Sciences
Clara Schmidt
Department of Financial Mathematics, University of Duisburg-Essen
Felix Weber
Center for Econometrics and Business Analytics, Johannes Gutenberg University Mainz
Haibo Wang
Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, 15213, USA

Published 2025-03-13

Keywords

  • Financial Risk Assessment,
  • Logistic Regression,
  • Statistical Modeling,
  • Risk Evaluation,
  • Empirical Analysis

How to Cite

Müller, H., Schmidt, C., Weber, F., & Wang, H. (2025). Logistic Regression-based method for Financial Risk Assessment. Economic and Financial Research Letters, 5(1). Retrieved from https://ojs.mri-pub.com/index.php/EFRL/article/view/109

Abstract

The importance of accurate financial risk assessment has been widely recognized in both academic research and practical applications. However, the existing methods often face challenges in terms of accuracy and efficiency. In response to this, this paper proposes a novel approach based on logistic regression for financial risk assessment. By incorporating key risk factors and applying advanced statistical modeling techniques, our method aims to improve the precision and timeliness of risk evaluation in financial decision-making processes. Through extensive empirical analysis and performance evaluation, we demonstrate the effectiveness and reliability of our proposed approach in capturing and predicting financial risks, providing valuable insights for risk management strategies in various financial sectors.

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