In this article, we encompass an analysis of the recent advances in parallel genetic
algorithms (PGAs). We have selected these algorithms because of the deep interest in many …

Despite the wide application of evolutionary computation (EC) techniques to rule discovery
in stock algorithmic trading (AT), a comprehensive literature review on this topic is …

Clustering is a fundamental and widely used method for grouping similar records in one
cluster and dissimilar records in the different cluster. In cluster analysis, a major problem is …

El presente trabajo tiene como objetivo comprobar la eficiencia débil en los 5 principales
mercados bursátiles de Latinoamérica, usando 2 enfoques; primero se evalúa la …

In recent years, algorithmic-based market manipulation in stock and power markets has
considerably increased, and it is difficult to identify all such manipulation cases. This causes …

Uno de los supuestos de los modelos de valoración de activos financieros es la presunción
de mercados bursátiles eficientes, en el presente trabajo se estudia la evolución de la …

This paper analyzes an open pit gold mine project based on the O'Hara cost model.
Hypothetical data is proposed based on different authors that have studied open pit gold …

The Genetic Algorithm (GA) is a relatively simple heuristic algorithm that can be
implemented in a straightforward manner. It can be applied to a wide variety of problems …

Many popular clustering techniques including K-means require various user inputs such as
the number of clusters k, which can often be very difficult for a user to guess in advance …

Financial time-series forecasting, and profit maximization is a challenging task, which has
attracted the interest of several researchers and is immensely important for investors. In this …