Bayesian regularized artificial neural networks for the estimation of the probability of default
E Sariev, G Germano - Quantitative Finance, 2020 - Taylor & Francis
… which the estimation of the network weights is performed. The first step in the estimation
process of … Our estimation approach provides objectivity to the estimation and reduces the bias. …
process of … Our estimation approach provides objectivity to the estimation and reduces the bias. …
An investigation of credit card default prediction in the imbalanced datasets
… Different traditional statistical models, including regression, nearest neighbor, and multiple
discriminant analysis, were not given significant results as compared to machine learning …
discriminant analysis, were not given significant results as compared to machine learning …
Partial default
C Arellano, X Mateos-Planas… - Journal of Political …, 2023 - journals.uchicago.edu
… narrative analysis for two default episodes in richer detail and argue that the flexibility of our
accounting framework allows us to summarize the salient features of these episodes. Some …
accounting framework allows us to summarize the salient features of these episodes. Some …
Corporate default forecasting with machine learning
… variety of methods for the estimation of default probabilities; linear discriminant analysis and
logistic regression are the most popular. The linear discriminant analysis (LDA) provides an …
logistic regression are the most popular. The linear discriminant analysis (LDA) provides an …
[PDF][PDF] Effect of Loan Default Rate on Financial Performance of Savings and Credit Cooperative Societies Innarok, County Kenya
KE Salaton, P Gudda, G Rukaria - International Journal of Academic …, 2020 - academia.edu
… the effect of loan default rate on financial performance of SACCOs in Narok County. Specifically
the study sought to determine the effect of loan default rate on financial performance of …
the study sought to determine the effect of loan default rate on financial performance of …
How to Reshape the Selection Boundaries between Traditional and Digital Supply Chain Finance Based on the Pledge Rate and Default Loss: Two Tripartite Game …
X Sun, Y Wang, Y Huang, Y Zhang - Systems, 2024 - search.ebscohost.com
… the sensitivity analysis of the endogenous factors such as pledge rate and default loss on …
, namely pledge rate and default loss, this paper conducts sensitivity analysis on the system …
, namely pledge rate and default loss, this paper conducts sensitivity analysis on the system …
Environmental, social and governance disclosure and default risk
… Hence, as part of our identification strategy, we address these endogeneity concerns in
three ways. First, we employ lagged independent variables to control for reverse causality. …
three ways. First, we employ lagged independent variables to control for reverse causality. …
Prediction of loan behaviour with machine learning models for secure banking
… of Ensemble Boosting approaches, to determine the accuracy of our predictive model's …
As a result of the bank loan default study utilized in this article, default goal values are binary…
As a result of the bank loan default study utilized in this article, default goal values are binary…
The differential impact of leverage on the default risk of small and large firms
… Our second contribution is an analysis of the influence of leverage on the probability of
recovery from the state of insolvency. Here, as in the Orbis database, “Insolvency” is used to refer …
recovery from the state of insolvency. Here, as in the Orbis database, “Insolvency” is used to refer …
Multi-class misclassification cost matrix for credit ratings in peer-to-peer lending
… study is to determine the values of misclassification costs by incorporating profit losses and
other … We adopt a quadratic programming to deduce loss given default (Lgd) backward from …
other … We adopt a quadratic programming to deduce loss given default (Lgd) backward from …