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 weights of a portfolio of high-frequency market indices. The information measure gathered from the markets produces reliable estimates of the weights at varying temporal horizons. The portfolio exhibits a high level of diversity, robustness and stability as not affected by the drawbacks of traditional mean-variance approaches.

Inferring multi-period optimal portfolios via detrending moving average cluster entropy / Murialdo, P.; Ponta, L.; Carbone, A.. - In: EUROPHYSICS LETTERS. - ISSN 0295-5075. - ELETTRONICO. - 133:6(2021), p. 60004. [10.1209/0295-5075/133/60004]

Inferring multi-period optimal portfolios via detrending moving average cluster entropy

Murialdo P.;Carbone A.
2021

Abstract

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 weights of a portfolio of high-frequency market indices. The information measure gathered from the markets produces reliable estimates of the weights at varying temporal horizons. The portfolio exhibits a high level of diversity, robustness and stability as not affected by the drawbacks of traditional mean-variance approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2914754