In this study, we address the ambiguity in portfolio optimization, particularly focusing on the uncertainty related to the statistical parameters governing asset returns. We propose a novel method that combines robust optimization with artificial neural networks (ANNs). Our approach effectively...

Logistic regression is widely used in complex data analysis. When predictors are at individual level and the response at aggregate level, logistic regression can be estimated using the Maximum Likelihood Estimation (MLE) method with the joint likelihood function formed by Poisson binomial...

This study evaluates the effectiveness of the Non-dominated Sorting Genetic Algorithm III (NSGA-III) in comparison to the traditional Mean-Variance optimization method for financial portfolio management. Leveraging a dataset of global financial assets, we applied both approaches to optimize...