We propose a dynamic method to hedge foreign exchange risk of international equity
portfolios. The method is based on the currency return forecasts derived from a set of …

ABSTRACT Complex Machine Learning (ML) models used to support decision-making in
peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While …

Online prediction of real-time taxi-hailing demand generally provides better real-time
decision support for passengers and taxi drivers compared with offline prediction. Current …

We propose a method for characterizing the local structure of weighted multivariate time
series networks. We draw intensity and coherence of network motifs, ie statistically recurrent …

We propose to investigate the joint dynamics of regional gross domestic product and life
expectancy in Italy through Wasserstein barycenter regression derived from optimal …

This article addresses the challenge of efficiently managing datasets of various sizes
through two key strategies: 1) dataset compression and 2) synthetic augmentation. This …

In this paper we provide a framework to study the network topology of generalized forecast
error variance decomposition (GFEVD) derived from multi-country, multi-variable time series …

We explore the potential of machine learning (ML) models applied in two financial risk
management areas, ie, credit risk management and financial risk hedging, through two …

In this paper, we study the second and third order cumulants of bilinear models with regime
changes according to a Markov chain (MS− BL for short). We provide conditions for the …

Modern time series analysis is facing the increasing availability of multidimensional data
generated over time. In finance, co-movements can be observed, for instance, across …