The Steiner tree problem aims to determine a minimum edge-weighted tree spanning a given set of terminal vertices from a given graph. As a popular model for numerous practical applications, the problem has been the object of two important competitions (the 11th DIMACS Challenge in 2014 and the...

We propose a novel methodology for modeling and forecasting multivariate realized volatilities using graph neural networks. This approach extends the work of Zhang et al. [2022] (Graph-based methods for forecasting realized covariances) and explicitly incorporates the spillover effects from...

Portfolio optimization is a pertinent topic of significant importance in the financial literature. During the portfolio construction, an investor confronts two important steps: portfolio selection and portfolio allocation. This article seeks to investigate portfolio optimization based on the...

We analyze the relationships within the liquid fuels system and its associated supply chain using innovative network filtering methods, namely the Minimum Spanning Tree and Triangulated Maximally Filtered Graph. Our findings reveal that biofuels form robust connections with their feedstocks that...

Several countries of the world are involved in mutual and collaborative business of military equipments, weapons in terms of their production, sales, technical maintenance, training and services. As a consequence, manufacturing of boms, rockets, missiles and other ammunitions have taken...

This paper contributes to the financial crisis literature by developing a deep learning model for predicting financial crisis events. We propose a novel gated graph neural network (GGNN) early warning model based on information spillover networks. The spillover network allows us to clarify the...

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rules may influence the diversification benefits of portfolios. The problem arises naturally in the area of Environmental, Social, and Governance...