  Despite half a century of research, there is still no general agreement about
the optimal approach to build a robust multi-period portfolio. We address this
question by proposing the detrended cluster entropy approach to estimate the
portfolio weights of high-frequency market indices. The information measure
produces reliable estimates of the portfolio weights gathered from the
real-world market data at varying temporal horizons. The portfolio exhibits a
high level of diversity, robustness and stability as it is not affected by the
drawbacks of traditional mean-variance approaches.
