7,189 research outputs found

    Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables

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    The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on default prediction has yet focused on micro-entities (MEs), despite such firms’ importance in the global economy. This paper builds the first bankruptcy model especially designed for MEs by using a wide set of accounts from 1999 to 2008 and applying artificial neural networks (ANNs). Our findings show that ANNs outperform the traditional logistic regression (LR) models. In addition, we also report that, thanks to the introduction of non-financial predictors related to age, the delay in filing accounts, legal action by creditors to recover unpaid debts, and the ownership features of the company, the improvement with respect to the use of solely financial information is 3.6%, which is even higher than the improvement that involves the use of the best ANN (2.6%)

    El poder temporal del papa, segĂșn RamĂłn Llull, y postura de Ă©ste relativa a las controversias de su tiempo

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    El Beato RamĂłn Llull en sus relaciones con la Escuela Franciscana de los siglos XIII-XIV

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    El Beato RamĂłn Llull en sus relaciones con la Escuela Franciscana de los siglos XIII-XIV

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    La "Donatio Constantini" en los escritos y en la mente de RamĂłn Llull

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    Hybrid model using logit and nonparametric methods for predicting micro-entity failure

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    Following the calls from literature on bankruptcy, a parsimonious hybrid bankruptcy model is developed in this paper by combining parametric and non-parametric approaches.To this end, the variables with the highest predictive power to detect bankruptcy are selected using logistic regression (LR). Subsequently, alternative non-parametric methods (Multilayer Perceptron, Rough Set, and Classification-Regression Trees) are applied, in turn, to firms classified as either “bankrupt” or “not bankrupt”. Our findings show that hybrid models, particularly those combining LR and Multilayer Perceptron, offer better accuracy performance and interpretability and converge faster than each method implemented in isolation. Moreover, the authors demonstrate that the introduction of non-financial and macroeconomic variables complement financial ratios for bankruptcy prediction

    El Papa 'Vicarius Petri' en RamĂłn Llull. Origen, vicisitudes y justificaciĂłn del tĂ­tulo papal

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    "Eclessia" y "Christianitas" en Inocencio III

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    El papa "vicarius Petri" en Ramon Llull (Origen, vicisitudes y justificacidn del tĂ­tulo papal)

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