Machine Learning (ML) excels at most predictive tasks but its complex nonparametric structure renders it less useful for inference and out‐of sample predictions. This article aims to elucidate and enhance the analytical capabilities of ML in real estate through Interpretable ML (IML)....

While Machine Learning (ML) excels at predictive tasks, its inferential capacity is limited due to its complex non-parametric structure. This paper aims to elucidate the analytical behavior of ML through Interpretable Machine Learning (IML) in a real estate context. Using a hedonic ML approach...

Purpose: The purpose of this paper is to contribute to the literature on seasoned equity offerings (SEOs) by examining the underpricing of European real estate corporations and identifying determinants explaining the phenomenon of setting the offer price at a discount at SEOs....