This paper proposes a new approach toward understanding the financial performance
dynamics in the EU retail sector (pre-pandemic); we focus on the connection between …

We construct a sovereign default network by employing high-dimensional vector
autoregressions obtained by analyzing connectedness in sovereign credit default swap …

Identifying the influential variables that provide early warning of financial network instability
is challenging, in part due to the complexity of the system, uncertainty of a failure, and …

Financial crisis prediction (FCP) received significant attention in the financial sector for
decision-making. Proper forecasting of the number of firms possible to fail is important to …

The presence of machine learning, data mining and related disciplines is increasingly
evident in everyday environments. The support for the applications of learning techniques in …

This paper addresses the critical challenge of detecting financial crises in their early stages
given their profound economic and societal consequences. It investigates the efficacy of …

The purpose of this study is to design a financial stress index to predict the occurrence of
financial crisis in the Tehran Stock Exchange. In this paper, a composite index has been …

This paper explores the transformative impact of artificial intelligence (AI) on portfolio
optimization in the financial sector. It examines how machine learning algorithms have …

We introduce a novel methodology to capture and represent the diverse relationships
between financial market institutions to prevent and mitigate negative economic shocks. An …

Today, Artificial Intelligence (AI) and Machine Learning/Deep Learning (ML/DL) have
become the hottest areas in information technology. In our society, many intelligent devices …