Cover Image

Combining Sampling Methods, Cost‐Sensitive Learning, and Ensemble Techniques for Highly Class‐Imbalanced Financial Distress Prediction

Fuente: Wiley Open Access

Saved in:

Bibliographic Details
Main Authors:	Wei‐Qiang Huang, Lianlian Wang
Format:	Artículo Open Access
Published:	Wiley 2026
Subjects:	Journal of Forecasting
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data Quality Improvement for Financial Distress Prediction: Feature Selection, Data Re‐Sampling, and Their Combinations in Different Orders
by: Chih‐Fong Tsai, et al.
Published: (2025)

Deep Dive Into Churn Prediction in the Banking Sector: The Challenge of Hyperparameter Selection and Imbalanced Learning
by: Vasileios Gkonis, et al.
Published: (2024)

Image‐Based Deep Learning Models for Stock Predictions: Combining Line, Candlestick, and Bar Charts
by: Wei‐Chao Lin, et al.
Published: (2026)

Enhancing Financial Tail Risk Forecasting: A Blending Ensemble Framework for Nonlinear Expectile Regression
by: Yaolan Ma, et al.
Published: (2026)

Innovative Techniques to Predict Churn in the French Insurance Industry: Integration of Machine Learning With the Grabit Model
by: Christophe Schalck, et al.
Published: (2025)

Ensemble Multitask Prediction of Air Pollutants Time Series: Based on Variational Inference, Data Projection, and Generative Adversarial Network
by: Kang Wang, et al.
Published: (2024)

Random Integrated Subdata Ensemble Method for Key Variable Selection in Rare Event Setting
by: Ching‐Chi Yang, et al.
Published: (2026)

A Novel Multiclass Imbalance Classification Framework With Dynamic Evidential Fusion for Credit Rating
by: Wen‐hui Hou, et al.
Published: (2025)

A Quantification Approach of Changes in Firms' Financial Situation Using Neural Networks for Predicting Bankruptcy
by: Philippe du Jardin
Published: (2024)

Fire Prediction and Risk Identification With Interpretable Machine Learning
by: Shan Dai, et al.
Published: (2025)

Decomposing, Learning, and Predicting Realized Volatilities: A Comparison Analysis From the Global Stock Markets
by: Wei Zhou, et al.
Published: (2025)

Estimation of Constrained Factor Models for High‐Dimensional Time Series
by: Yitian Liu, et al.
Published: (2025)

Enhancing the Potential of Random Forest Technique With an Adaptive Horse Herd Optimization Framework for Electric Load Prediction
by: Manvi Mishra, et al.
Published: (2026)

Climate Change Risk and Financial Market Response: An International Evidence From Performance Forecasts by Financial Analysts
by: Cyrine Khiari, et al.
Published: (2025)

Forecasting Disaggregated Producer Prices: A Fusion of Machine Learning and Econometric Techniques
by: Soňa Benecká
Published: (2026)

Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques
by: Zin Mar Oo, et al.
Published: (2025)

On the Optimal Selection of Time‐Lag Embedding Dimension for Deep Learning Approaches in Financial Forecasting With Big Data
by: Mohammadreza Ghadimpour, et al.
Published: (2025)

Spread Option Pricing Method Based on Nonparametric Predictive Inference Copula
by: Ting He
Published: (2025)

Macroeconomic and Financial Forecasting in the Aftermath of the Covid Shock: Inflation Forecasting With Large Language Models
by: Nikolaos Giannellis, et al.
Published: (2026)

US Climate Shocks: The Double Risk for the Global Financial Stability
by: Brahim Gaies, et al.
Published: (2026)

Ternary Interval Forecasting of Air Pollutant Concentration: A Novel Multivariate Decomposition and Optimal Variable Weight Ensemble Paradigm
by: Zicheng Wang, et al.
Published: (2025)

A Dynamic Fuzzy Modeling Method for Interval Time Series and Applications in Range‐Based Volatility Prediction
by: Leandro Maciel, et al.
Published: (2025)

A New Multivariate Decomposition–Ensemble Approach With Multisource Heterogeneous Data for Crude Oil Price Forecasting
by: Zhengling Zhao, et al.
Published: (2026)

Measuring the Impact of Transition Risk on Financial Markets: A Joint VaR‐ES Approach
by: Laura Garcia‐Jorcano, et al.
Published: (2025)

Combine to compete: Improving fiscal forecast accuracy over time
by: Laura Carabotta, et al.
Published: (2024)

Common Mutual Information Selection Algorithm and Its Application on Combination Forecasting
by: Chenqing Shen, et al.
Published: (2024)

Predicting Equity Premium: A New Momentum Indicator Selection Strategy With Machine Learning
by: Yong Qu, et al.
Published: (2024)

Forecasting Life Cycle Costs of Weapon Systems: An Open Source Approach With Artificial Intelligence
by: Martín Díaz Cuesta, et al.
Published: (2026)

Dual‐Branch Spectral‐Trend Attention Network With Gated Flux–Momentum Decomposition for Multiscale Financial Time‐Series Forecasting
by: Pradeep Singh, et al.
Published: (2026)

A Hybrid Deep Learning Model for Coal Index Forecasting Based on Sentiment Analysis and Decomposition–Reconstruction Methods
by: Yi Xiao, et al.
Published: (2025)

Measuring the Default Risk of Small Business Loans: Improved Credit Risk Prediction Using Deep Learning
by: Yiannis Dendramis, et al.
Published: (2025)

A Two‐Stage Interpretable Model to Explain Classifier in Credit Risk Prediction
by: Lu Wang, et al.
Published: (2025)

Leveraging Machine Learning to Predict Food Waste Quantity: Focusing on Military Dining Facilities as Large‐Scale Food Service Operations
by: YongSun Kim, et al.
Published: (2026)

Media and Business Cycle Predictability
by: Salim Baz, et al.
Published: (2026)

Forecasting realized volatility of crude oil futures prices based on machine learning
by: Jiawen Luo, et al.
Published: (2024)

Combined Effects of Fat‐Tail and Spread Forecasting on Pairs Trading: A Hybrid Model Based on Integrating VAR With GRU Models
by: Yuhee Kwon, et al.
Published: (2025)

A Review of Methods for Long‐Term Electric Load Forecasting
by: Thangjam Aditya, et al.
Published: (2024)

On Capturing Multi‐Scale Market Dynamics for High‐Frequency Stock Price Forecasting Using a Hybrid Attention‐Based Deep Learning Model
by: Runze Jiang, et al.
Published: (2026)

Debiasing UTO Estimator: Methods and Application to Climate Change Data Sets
by: Gülesen Üstündağ Şiray, et al.
Published: (2026)

Validating Explainer Methods: A Functionally Grounded Approach for Numerical Forecasting
by: Felix Haag, et al.
Published: (2025)