This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the complexity-effectiveness balance of each methodology; identify a reduced set of independent variables that are significant predictors whatever the methodology is; and discuss and relate these findings to the financial theory, to help consolidate the foundations of a theory offinancialfailure. Our results indicate that, whatever the methodology is, reliable predictions can be made using four variables; these ratios convey information about profitability, financial structure, rotation, and op...
This article is addressed from the strategic perspective in finances; its goal is to show recent tec...
The following work seeks to evaluate traditional methodologies of time series forecasting compared t...
The purpose of this work is to model and predict Financials Time Series by using neural networks. In...
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: ...
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: ...
This paper offers an exhaustive analysis of the effectiveness of several models and methodologies th...
We are interested in forecasting bankruptcies in a probabilistic way. Specifcally, we com- pare the ...
Predicting corporate failure is an important problem in management science. This study tests a new m...
Predicting corporate failure is an important problem in management science. This study tests a new m...
This paper shows how the forecast affects reducing the number of variables with which the prediction...
Este trabajo replica y adapta el modelo de Jones y Hensher (2004) a los datos de una economía emerge...
In the present decade, in emerging economies such as those in Latin-America, mixed logistic models h...
Prediction of insurance companies insolvency has arisen as an important problem in the field of fina...
This paper contains a financial forecast using Artificial Neural Networks. The analysis used the tra...
Este trabajo intenta profundizar en los factores queinfluyen en la aparición de crisis financieras. ...
This article is addressed from the strategic perspective in finances; its goal is to show recent tec...
The following work seeks to evaluate traditional methodologies of time series forecasting compared t...
The purpose of this work is to model and predict Financials Time Series by using neural networks. In...
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: ...
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: ...
This paper offers an exhaustive analysis of the effectiveness of several models and methodologies th...
We are interested in forecasting bankruptcies in a probabilistic way. Specifcally, we com- pare the ...
Predicting corporate failure is an important problem in management science. This study tests a new m...
Predicting corporate failure is an important problem in management science. This study tests a new m...
This paper shows how the forecast affects reducing the number of variables with which the prediction...
Este trabajo replica y adapta el modelo de Jones y Hensher (2004) a los datos de una economía emerge...
In the present decade, in emerging economies such as those in Latin-America, mixed logistic models h...
Prediction of insurance companies insolvency has arisen as an important problem in the field of fina...
This paper contains a financial forecast using Artificial Neural Networks. The analysis used the tra...
Este trabajo intenta profundizar en los factores queinfluyen en la aparición de crisis financieras. ...
This article is addressed from the strategic perspective in finances; its goal is to show recent tec...
The following work seeks to evaluate traditional methodologies of time series forecasting compared t...
The purpose of this work is to model and predict Financials Time Series by using neural networks. In...