This study examines the application of machine learning models to predict financial performance in various sectors, using data from 21 companies listed in the BIST100 index (2013-2023). The primary objective is to assess the potential of these models in improving financial forecast accuracy and...

Leib et al. (2024) examine how artificial intelligence (AI) generated advice affects dishonesty compared to equivalent human advice in a laboratory experiment. In their preferred empirical specification, the authors report that dishonesty-promoting advice increases dishonest behavior by...

When inter-arrival times between events follow an exponential distribution, this implies a Poisson frequency of events, as both models assume events occur independently and at a constant average rate. However, these assumptions are often violated in real-insurance applications. When the rate at...

Investigating how systemic risk originates and spreads across the financial system poses an inherently compositional question, i.e., a question concerning the joint distribution of relative risk share across several interdependent contributors. To address this question, we propose a weighted...