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Using a large panel of US banks over the period 2008-2013, this paper proposes an early warning framework to identify bank heading to bankruptcy. We conduct a comparative analysis based on both Canonical Discriminant Analysis and Logit models to examine and to determine the most accurate one....
Persistent link: https://www.econbiz.de/10012968419
This study is intended to identify the predictors of financial distress for the Pakistani firms. Variables used are the financial ratios representing profitability, liquidity, leverage, and cash flows, as well as two important market factors which are size and idiosyncratic standard deviation of...
Persistent link: https://www.econbiz.de/10012023254
We develop a model of neural networks to study the bankruptcy of U.S. banks. We provide a new model to predict bank defaults some time before the bankruptcy occurs, taking into account the specific features of the current financial crisis. Based on data from the Federal Deposit Insurance...
Persistent link: https://www.econbiz.de/10013135648
Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by integrated Multi Layered Perceptron with Imperialist Competitive Algorithm (MLP-ICA) and Kohonen self...
Persistent link: https://www.econbiz.de/10013006207
In this study we tried to compare two models in order to identify optimal neural networks models in predicting bankruptcy. Multi-layered perceptron (MLP) because of easy training and high efficiency and also integrated multi-layered perceptron (most used neural network in predicting bankruptcy)...
Persistent link: https://www.econbiz.de/10013051202
A financial market can be expressed in a network structure where the stocks resides as nodes and the links account for returns correlation. Centrality measure in the financial network structure captures firms' embeddedness and connectivity in the capital market structure. This paper investigates...
Persistent link: https://www.econbiz.de/10013021792
The paper deals with the topic of modelling the probability of bankruptcy of Polish enterprises using convolutional neural networks. Convolutional networks take images as input, so it was thus necessary to apply the method of converting the observation vector to a matrix. Benchmarks for...
Persistent link: https://www.econbiz.de/10012799240
In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models, by maximizing their discriminatory power as measured by the Area Under Receiver Operating Characteristics (AUROC) curve. A method is introduced and compared with traditional...
Persistent link: https://www.econbiz.de/10013225542
The purpose of this article is the presentation of a novel and unconventional algorithm for bankruptcy risk management in banking technologies catered towards lending to legal entities (enterprises and companies). The challenges of assessing risk in this area primarily relate to the reduction of...
Persistent link: https://www.econbiz.de/10012830011
This paper shows the evolution of financial distress prediction models of the past four decades. Special attention is paid to linear discriminant analyses, logistic regression analyses and neural networks. Based on accounting data of 50 UK industrial firms, prediction models are estimated using...
Persistent link: https://www.econbiz.de/10012946424