We examine foreclosure discounts and their subsequent impact on investor returns in Berlin's housing market from 1984 to 2022. Utilizing hedonic regression models and matching techniques on a data set of housing transactions, we determine that foreclosure discounts, ranging from 20% to 50%, are...

Forecasting changes in stock prices is extremely challenging given that numerous factors cause these prices to fuctuate. The random walk hypothesis and efcient market hypothesis essentially state that it is not possible to systematically, reliably predict future stock prices or forecast changes...

This study investigates the simplicity and adequacy of tail-based risk measures-valueat-risk (VaR) and expected shortfall (ES)-when applied to tail targeting of the extreme value (EV) model. We implement Lévy-VaR and ES risk measures as full density-based alternatives to the generalized Pareto...

In the feld of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction efects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting diferent measures of stock...