Forecasting Financial Distress for Shaping Public Policy: An Empirical Investigation

Forecasting Financial Distress for Shaping Public Policy: An Empirical Investigation

Background: Prediction of financial distress has been made more accurate and reliable through machine learning methods. Financial stress affects the business corporate entity, society and the general economy. Analysing such nonlinear events is essential for preventing the dangers and supporting a fa...

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Bibliographic Details
Main Authors: Soumya Ranjan Sethi, Dushyant Ashok Mahadik
Format: Article
Language:English
Published: Prague University of Economics and Business 2025-01-01
Series:Acta Informatica Pragensia
Subjects:
forecasting
public policy
sustainability
ann
future cash flow
fcf
logistic regression
lr
linear discriminant analysis
lda
Online Access:https://aip.vse.cz/artkey/aip-202501-0004_forecasting-financial-distress-for-shaping-public-policy-an-empirical-investigation.php
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https://aip.vse.cz/artkey/aip-202501-0004_forecasting-financial-distress-for-shaping-public-policy-an-empirical-investigation.php

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