Recent studies highlight the superior performance of non-linear machine learning models, such as neural networks, over …-linear interactions between predictive signals and future returns. This thesis researches whether sector-specific neural networks can … at the stock level and in portfolios based on return forecasts, constructing long-short portfolios from the networks …

Understanding the balance between structure and flexibility in innovation networks is critical for optimizing … characteristics, challenges, and indicators of formality within formal and informal innovation networks. Formal networks are defined … by hierarchical structures, contractual governance, and regulated communication channels, while informal networks thrive …

is yet to be explored. In this paper, we discuss the use of neural networks to set the price of health insurance coverage … following the structure of a classical frequency-severity model. In particular, we propose negative multinomial neural networks … to jointly model the frequency of possibly correlated medical claims and Gamma neural networks to estimate the expected …

. We use machine learning and Graph Convolutional Networks (GCNs) to optimize the maintenance schedules for railway …