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...

This paper is concerned with simulation based inference in generalized models of stochastic volatility defined by heavy-tailed student-t distributions (with unknown degrees of freedom) and covariate effects in the observation and volatility equations and a jump component in the observation...