This study explores the main characteristics of the business bankruptcy phenomenon. Some financial ratios are analysed in the context of bankruptcy prediction in Portuguese textile industry, using statistical instruments of multivariate analysis, particularly the discriminant analysis and the...

Prediction of corporate bankruptcy is a phenomenon of increasing interest to investors/creditors, borrowing firms, and governments alike. Timely identification of firms' impending failure is indeed desirable. By this time, several methods have been used for predicting bankruptcy but some of them...

Bankruptcy is a menacing situation, which the investors, businesses, and the economy are afraid of, due to its adverse effects. Prediction of bankruptcy can help the investors and businesses in formulating their strategies in order to improve their profits or at least avoid losses. Researchers...

Quite a few in-depth articles were found in the above-mentioned domain. Bankruptcy is one of the most critical factors which most of companies don't want to face. To predict the Bankruptcy of Banks, there have been several attempts made, some have been successful and some are coming up with new...

The research focuses on the financial turmoil, pursuing different methods to foretell such turmoil. Besides, the methods are undertaken from (McCulloch and Pitts 1943) and ended till (Hosaka 2019). The evidence from such a comprehensive analysis pointed to the use of various ratios using...

This paper analyzes a family of multivariate point process models of correlated event timing whose arrival intensity is driven by an affine jump diffusion. The components of an affine point process are self- and cross-exciting, and facilitate the description of complex event dependence...

This paper focuses on the development of both failure prediction models on a paired sample and a random sample of small and medium-sized firms with head offices located in the region of Castilla y León (Spain), in order to prove if the predictive power of the developed models is affected by the...

This paper proposes a machine learning approach to estimate physical forward default intensities. Default probabilities are computed using artificial neural networks to estimate the intensities of the inhomogeneous Poisson processes governing default process. The major contribution to previous...

The purpose of this paper is to derive a model for calculation of maturities and volumes of repayments that a bank may expect from nonretail nonperforming loans (hereafter NPLs). Expected inflows from nonretail NPLs follow a probability distribution, defined by size and timing of historic...