Insolvency Forecasting through Trend Analysis with Full Ignorance of Probabilities

Tomáš Poláček,Markéta Kruntorádová

doi:10.18267/j.aop.625

Abstract

Insolvency Forecasting through Trend Analysis with Full Ignorance of Probabilities

Highlights

At this time, along with the increasing number of insolvency proceedings, efforts are being made to streamline processes and identify links between majority creditors (Mrázová and Zvirinský, 2015)
Some studies are focused on the descriptive state of the domestic market over a certain period after the introduction of the Insolvency Act (Smrčka, Schőnfeld and Ševčík, 2013) or what effect the amendments and amendments to the act itself have on the practice, which addressed some of the fundamental issues regarding powers in decision-making in insolvency proceedings (Richter, 2013)
A broad spectrum of research activities in artificial intelligence has generated many different methods, algorithms and methodologies, which can potentially be used for forecasting and related areas

Summary

Introduction

Along with the increasing number of insolvency proceedings, efforts are being made to streamline processes and identify links between majority creditors (Mrázová and Zvirinský, 2015). Insolvency proceedings as such are subject to the influence of many factors from the whole economic environment. The use of trend research is appropriate (Vícha and Dohnal, 2008; Dohnal, 2016) This means that knowledge items of different levels of subjectivity must be taken into consideration to develop the best possible model of a unique task under study. This is the reason why information non-intensive formal tools are used more and more frequently, see e.g. fuzzy and/or rough sets (Pavláková Dočekalová and Kocmanová, 2016; Meluzín et al, 2016)

Alternative Decision-Making Methods in the Process

Trend Models

Transitional Graphs

Case Study

Model of Insolvency Proceedings

Probability Distributions

Conclusion