This paper presents a study of Artificial Neural Network (ANN) and Bayesian Network (BN) for use in stock index prediction. The data from Nigerian Stock Exchange (NSE) market are applied as a case study. Based on the rescaled range analysis, the neural network was used to capture the...

This article aims to identify the most relevant variables that allow through a neural network model (RNA), with supervised learning, in a kind of error correction and feedforward perceptron multilayer architecture to achieve the best predictors of low risk, in the process of microcredit....

The level of default in financial institutions is a key piece of information in the activity of these organizations and reveals their level of risk. This in turn explains the growing attention given to variables of this kind, during the crisis of these last years. This paper presents a method to...

Fraudulent financial reporting is a matter of great social and economic concern. Managers may distort financial statements so as to present their companies more favorably to investors or creditors. On the other hand, auditors are the ones who are expected to identify fraudulent financial...

Econometric models, in the estimation of real estate prices, are a useful and realistic approach for buyers and for local and fiscal authorities. From the classical hedonic models to more data driven procedures, based on Artificial Neural Networks (ANN), many papers have appeared in economic...