This paper offers an exhaustive analysis of the effectiveness of several models and methodologies that are commonly used to forecast financial failure: Linear, MDA, Logit, and artificial neural network. Our main aim is to evaluate their relative strengths and weaknesses, in terms of technical...

We evaluate the prediction accuracy of models designed using different classification methods depending on the technique used to select variables, and we study the relationship between the structure of the models and their ability to correctly predict financial failure. We show that a neural...

En este artículo aportamos evidencia empírica de predicción del fallo financiero en empresas no financieras. Hemos desarrollado diversos modelos para la evaluación del riesgo de fallo financiero en PYME. Contrastada la capacidad predictiva de modelos paramétricos (análisis discriminante...

We introduce the conditional restricted Boltzmann machine as method to analyze brand-level market basket data of individual households. The conditional restricted Boltzmann machine includes marketing variables and household attributes as independent variables. To our knowledge this is the first...

We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses unsupervised representation learning and a novel mode contrastive autoencoder to group episodes...

El objetivo del presente trabajo de investigación es mostrar el impacto de las amenazas de la inundación, la sequía y la helada en el bienestar de las diferentes regiones de Bolivia, tomando a las vulnerabilidades como variables de aproximación a los indicadores socioeconómicos de...

Financial authorities' use of technology has evolved over the years, leading to different generations of technology that culminate in what the paper considers as suptech. Suptech refers to the application of big data or artificial intelligence (AI) to tools used by financial authorities. There...

This paper presents an original classifier model based on an artificial neural network (ANN) architecture that is able to learn a specific human behavior and can be used in different socio-economic systems. After a training process, the system can identify and classify a human subject using a...

Having forecast of real estate sales done correctly is very important for balancing supply and demand in the housing market. However, it is very difficult for housing companies or real estate professionals to determine how many houses they will sell next year. Although this does not mean that a...

El estudio de las disfunciones financieras de las empresas ha sido un tópico común en la investigación a lo largo de las últimas décadas; no obstante, algunos aspectos de los procesos de fracaso han recibido relativamente poca atención. Este trabajo profundiza en su dimensión temporal....