Estimation errors in the inputs are the main problem when applying portfolio analysis, and Markov regime switching models have been shown to reduce these errors. We investigate whether the use of two regime models remains superior across a range of values of risk aversion and transaction costs,...

We examine the diversification benefits of cryptocurrency asset categories. To mitigate the effects of estimation risk, we employ the Bayes-Stein model with no short-selling and variance-based constraints. We estimate the inputs using lasso regression and elastic net regression, employing the...

This paper uses a novel numerical optimization technique – robust optimization – that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach...