A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms
Y Shi, X Li - Heliyon, 2019 - cell.com
Bibliometric analysis is an effective method to carry out quantitative study of academic output
to address the research trends on a given area of investigation through analysing existing …
to address the research trends on a given area of investigation through analysing existing …
Systematic review of financial distress identification using artificial intelligence methods
The study presents a systematic review of 232 studies on various aspects of the use of
artificial intelligence methods for identification of financial distress (such as bankruptcy or …
artificial intelligence methods for identification of financial distress (such as bankruptcy or …
CatBoost model and artificial intelligence techniques for corporate failure prediction
Financial distress prediction provides an effective warning system for banks and investors to
correctly guide decisions on granting credit. Ensemble methods have demonstrated their …
correctly guide decisions on granting credit. Ensemble methods have demonstrated their …
Research on financial early warning of mining listed companies based on BP neural network model
X Sun, Y Lei - Resources Policy, 2021 - Elsevier
Mining industry is the basic industry of the national economy. However, in recent years,
listed mining companies have suffered serious financial risks due to special reasons such as …
listed mining companies have suffered serious financial risks due to special reasons such as …
Bankruptcy prediction using the XGBoost algorithm and variable importance feature engineering
The emergence of big data, information technology, and social media provides an enormous
amount of information about firms' current financial health. When facing this abundance of …
amount of information about firms' current financial health. When facing this abundance of …
The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning
This study aims to predict oil prices during the 2019 novel coronavirus (COVID-19)
pandemic by looking into green energy resources, global environmental indexes (ESG), and …
pandemic by looking into green energy resources, global environmental indexes (ESG), and …
Multi-class financial distress prediction based on support vector machines integrated with the decomposition and fusion methods
Binary financial distress prediction (FDP), which categorizes corporate financial status into
the two classes of distress and nondistress, cannot provide enough support for effective …
the two classes of distress and nondistress, cannot provide enough support for effective …
Predicting the changes in the WTI crude oil price dynamics using machine learning models
H Guliyev, E Mustafayev - Resources Policy, 2022 - Elsevier
This study aims to use a monthly dataset from 1991 to 2021 to predict West Texas
Intermediate (WTI) oil price dynamics using US macroeconomic and financial factors, as well …
Intermediate (WTI) oil price dynamics using US macroeconomic and financial factors, as well …
Management of financial risks in Slovak enterprises using regression analysis
Research background: Financial risk management is the task of monitoring financial risks
and managing their impact. Financial risk is often perceived as the risk that a company may …
and managing their impact. Financial risk is often perceived as the risk that a company may …
Financial risk measurement and prediction modelling for sustainable development of business entities using regression analysis
The issue of the debt, bankruptcy or non-bankruptcy of a company is presented in this article
as one of the ways of conceiving risk management. We use the Amadeus database to obtain …
as one of the ways of conceiving risk management. We use the Amadeus database to obtain …