Predicting financial distress in Latin American companies : a comparative analysis of logistic regression and random forest models
Year of publication: |
2024
|
---|---|
Authors: | Barboza, Flavio Luiz de Moraes ; Altman, Edward I. |
Subject: | Corporate default | Credit risk | Distress prediction | Logistic regression | Random forest | Kreditrisiko | Regressionsanalyse | Regression analysis | Insolvenz | Insolvency | Prognoseverfahren | Forecasting model | Lateinamerika | Latin America | Logit-Modell | Logit model |
-
Khemais, Zaghdoudi, (2016)
-
Local logit regression for loan recovery rate
Sopitpongstorn, Nithi, (2021)
-
P2P lending scoring models : do they predict default?
Giudici, Paolo, (2018)
- More ...
-
Machine learning predictivity applied to consumer creditworthiness
Aniceto, Maisa Cardoso, (2020)
-
Board structure and financial distress in Brazilian firms
Freitas Cardoso, Guilherme, (2019)
-
A review of artificial intelligence quality in forecasting asset prices
Barboza, Flavio Luiz de Moraes, (2023)
- More ...