We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

Industry classification groups firms into finer partitions to help investments and empirical analysis. To overcome the well-documented limitations of existing industry definitions, like their stale nature and coarse categories for firms with multiple operations, we employ a clustering approach...

Bonds issued in high and low interest-rate environments often list at different prices despite very similar characteristics. From a risk-neutral investor's perspective, higher current prices imply higher losses in case of default, which must be compensated, if markets are efficient. We call this...

Bonds issued in high and low interest-rate environments often list at different prices despite very similar characteristics. From a risk-neutral investor's perspective, higher current prices imply higher losses in case of default, which must be compensated, if markets are efficient. We call this...