Robust international portfolio optimization with worst‐case mean‐CVaR

We propose a robust international portfolio optimization model in a worst-case mean-CVaR framework. In our model, we assume that the distributions, the first- and second-order moments of returns of assets and exchange rates are ambiguous. To control the conservatism of our robust model, we incorporate a new support set constructed by intervals of deviations from the no-arbitrage condition in currency markets into the ambiguity set of distribution. Our model can be reformulated as an equivalent semi-definite programming problem, which is computationally tractable. We conduct empirical experiments by the weekly rolling window strategy during the total period, the 1997 Asian Financial Crisis period, and the recent stable period. Using various performance measures, we investigate the out-of-sample performance of our model with comparison to those of other four benchmark models. The experimental results demonstrate that our model has the best performance in terms of return and various risk adjusted return measures during all of the three periods. They suggest that investors can obtain significant benefits when employing the robust portfolio strategy and the new support set, and considering the ambiguity of the first- and second-order moments during both volatile and stable periods.