Traditional approaches to the study of technical analysis (TA) often focus on the performance of a single indicator, which seems to fall short in scope and depth. We use a genetic algorithm (GA) to optimize trading strategies in the three major Forex markets, in order to verify the adequacy of...

Despite the obvious benefits and growing popularity of Machine Learning (ML) technology, there are still concerns regarding its ability to provide Financial Distress Prediction (FDP). An accurate FDP model is required to avoid financial risk at the lowest possible cost. However, in the Internet...

Risk interaction network (RIN), a system comprised of risk (nodes) and triggering relations (edges) between risks, changes the likelihood of occurring and also the impact of a risk. An issue of optimizing RIN, allowing for the risk response actions of weakening risk interactions, departs from...

This article exclusively formulates and presents three innovative hypotheses related to the execution of share buybacks, employing Genetic Algorithms (GAs) and mathematical optimization techniques. Drawing on the foundational contributions of scholars such as Osterrieder, Seigne, Masters, and...

The purpose of this study is to build a system that automatically generates an optimal strategy (AGOS) which can solve the business problem of maximizing the acceptance rate without taking more risks in loan approval process. This paper formulates the finding an optimal approval strategy of a...