We propose a novel regression approach for optimizing portfolios by means of Bayesian regularization techniques. In particular, we represent the weight deviations of the global minimum variance portfolio from a reference portfolio (e.g. the naive 1/N portfolio) as coefficients of a linear...

"This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using...

We investigate the impact of shrinkage estimation techniques for the moments of asset returns on risk-parity portfolios. In contrast to mean-variance portfolios, the risk contributions of individual assets in risk-parity portfolios are fixed a priori. This additional restriction stabilizes...