We propose a framework for combining portfolio rules while mitigating the impact of estimation error. Our main goal is to integrate heterogeneous rules that previously proposed combination methods are unable to accommodate, enabling researchers and investors to leverage established and ongoing...

We introduce a novel dynamic portfolio choice method, focusing on robust out-of-sample performance rather than on optimal in-sample performance. We therefore devise a strategy that rigorously tackles the problem of estimation error. The method involves defining a discrete set of single-period...