This study proposes a novel loss function for neural network models that explores the topological structure of stock realized volatility (RV) data by adding Wasserstein Distance (WD). The study shows that the proposed loss statistically significantly improves the forecast accuracy of neural network models …

Purpose All entrepreneurs interact simultaneously with multiple entrepreneurial contexts throughout their entrepreneurial journey. This conceptual paper has two central aims: (1) it synthesises the current literature on gender and entrepreneurship, and (2) it increases our understanding of how gender …

This research was conducted to update the content of the International Business Studies curriculum. The dynamically developing business environment, including the shift towards hybrid work, deepened the widely reported misalignment between business communication instruction and industry requirements. …

This paper addresses the challenge of assessing Energy Transition Readiness levels in businesses. It identifies gaps in existing literature concerning energy transitions and readiness levels. To tackle this, the paper employs organizational learning theory as its foundational model and introduces a new …

The role of central banks in addressing the emerging challenges posed by climate change has garnered significant attention from practitioners and academics alike. Through meticulous bibliometric analysis, this article reveals the fundamental themes and dynamic trends within this research field. Simultaneously, …

This paper presents a user-friendly version of Persistent Homology (PH) graph code to model financial market structures and changes. By leveraging Topological Data Analysis (TDA), the code offers an effective approach for analyzing high-dimensional stock data, enabling the identification of persistent …

This paper presents user-friendly code for the implementation of a loss function for neural network time series models that exploits the topological structures of financial data. By leveraging the recently-discovered presence of topological features present in financial time series data, the code offers …

In the constantly changing landscape of corporate sustainability, navigating the complex network of ESG reporting standards and frameworks has become a significant challenge for businesses worldwide. This research seeks to improve understanding of ESG reporting and shed light on the complexities of the …

This paper investigates the application of neural basis expansion analysis with exogenous variables (NBEATSx) in the prediction of daily stock realized volatility for various time steps. It compares NBEATSx’s forecasting accuracy and robustness with several commonly used models, namely Long-Short Term …

Purpose The concept of banking reputation has gained significant attention due to its relevance in the banking industry. A strong reputation has become crucial for a bank’s success, as it affects trust, credibility and stakeholders' perceptions. However, understanding and managing reputation in the banking …