Insolvency Forecasting through Trend Analysis with Full Ignorance of Probabilities

Abstract

The complex views of insolvency proceedings are unique, poorly known, interdisciplinary and multidimensional, even though there is a broad spectrum of different BM (Bankruptcy Models). Therefore, it is often prohibitively difficult to make forecasts using numerical quantifiers and traditional statistical methods. The least information-intensive trend values are used: positive, increasing, zero, constant, negative, decreasing. The solution of a trend model is a set of scenarios where X is the set of variables quantified by the trends. All possible transitions among the scenarios are generated. An oriented transitional graph has a set of scenarios as nodes and the transitions as arcs. An oriented path describes any possible future and past time behaviour of the bankruptcy system under study. The graph represents the complete list of forecasts based on trends. An eight-dimensional model serves as a case study. On the transitional graph of the case study model, decision tree heuristics are used for calculating the probabilities of the terminal scenarios and possible payoffs.The complex views of insolvency proceedings are unique, poorly known, interdisciplinary and multidimensional, even though there is a broad spectrum of different BM (Bankruptcy Models). Therefore, it is often prohibitively difficult to make forecasts using numerical quantifiers and traditional statistical methods. The least information-intensive trend values are used: positive, increasing, zero, constant, negative, decreasing. The solution of a trend model is a set of scenarios where X is the set of variables quantified by the trends. All possible transitions among the scenarios are generated. An oriented transitional graph has a set of scenarios as nodes and the transitions as arcs. An oriented path describes any possible future and past time behaviour of the bankruptcy system under study. The graph represents the complete list of forecasts based on trends. An eight-dimensional model serves as a case study. On the transitional graph of the case study model, decision tree heuristics are used for calculating the probabilities of the terminal scenarios and possible payoffs.