The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
The prediction of firm financial distress during the COVID-19 crisis episode attracted
massive academic attention since economic uncertainty was exacerbated. In this paper, we …
massive academic attention since economic uncertainty was exacerbated. In this paper, we …
Emerging trends in deep learning for credit scoring: A review
Y Hayashi - Electronics, 2022 - mdpi.com
This systematic review aims to provide deep insights on emerging trends in, and the
potential of, advanced deep learning techniques, such as machine learning algorithms …
potential of, advanced deep learning techniques, such as machine learning algorithms …
A novel deep neural network model based Xception and genetic algorithm for detection of COVID-19 from X-ray images
B Gülmez - Annals of Operations Research, 2023 - Springer
The coronavirus first appeared in China in 2019, and the World Health Organization (WHO)
named it COVID-19. Then WHO announced this illness as a worldwide pandemic in March …
named it COVID-19. Then WHO announced this illness as a worldwide pandemic in March …
Intelligent candlestick forecast system for financial time-series analysis using metaheuristics-optimized multi-output machine learning
The effective prediction of stock market prices and trends is a critical topic in financial
research for investors and stakeholders who wish to increase their return on investment …
research for investors and stakeholders who wish to increase their return on investment …
Predicting financial distress using current reports: A novel deep learning method based on user-response-guided attention
Effective financial distress prediction (FDP) can discover a company's potential financial
risks and support relevant decisions in a timely manner. Previous studies on FDP have …
risks and support relevant decisions in a timely manner. Previous studies on FDP have …
Exploring trends and advancements in financial distress prediction research: A bibliometric study
SR Sethi, DA Mahadik… - International Journal of …, 2024 - econjournals.com.tr
Due to the growing complexity and unpredictability of contemporary markets as evidenced
by the financial crisis of the past ten years, the field of financial distress prediction (FDP) …
by the financial crisis of the past ten years, the field of financial distress prediction (FDP) …
Cost-sensitive stacking ensemble learning for company financial distress prediction
S Wang, G Chi - Expert Systems with Applications, 2024 - Elsevier
Financial distress prediction (FDP) is a topic that has received wide attention in the finance
sector and data mining field. Applications of combining cost-sensitive learning with …
sector and data mining field. Applications of combining cost-sensitive learning with …
Enhancing credit risk prediction with hybrid deep learning and sand cat swarm feature selection
R Ramesh, M Jeyakarthic - Multimedia Tools and Applications, 2024 - Springer
Credit risk prediction method acts as a vital financial tool for measuring the default
probability of credit applicants. For financial institutions, proper credit risk management …
probability of credit applicants. For financial institutions, proper credit risk management …
A Hybrid Network Analysis and Machine Learning Model for Enhanced Financial Distress Prediction
ST Kadkhoda, B Amiri - IEEE Access, 2024 - ieeexplore.ieee.org
Financial distress prediction is crucial to financial planning, particularly amid emerging
uncertainties. This study introduces a novel methodology for predicting financial distress by …
uncertainties. This study introduces a novel methodology for predicting financial distress by …
Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models
The present paper aims to compare the predictive performance of five models namely the
Linear Discriminant Analysis (LDA), Logistic Regression (LR), Decision Trees (DT), Support …
Linear Discriminant Analysis (LDA), Logistic Regression (LR), Decision Trees (DT), Support …