| Issue |
EPL
Volume 133, Number 6, March 2021
|
|
|---|---|---|
| Article Number | 60004 | |
| Number of page(s) | 7 | |
| Section | General | |
| DOI | https://doi.org/10.1209/0295-5075/133/60004 | |
| Published online | 12 May 2021 | |
Inferring multi-period optimal portfolios via detrending moving average cluster entropy(a)
1 Politecnico di Torino - corso Duca degli Abruzzi 24, 10129 Torino, Italy
2 Università Cattaneo LIUC - Castellanza (VA), Italy
Received: 31 January 2021
Accepted: 4 March 2021
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.
PACS: 05.40.-a – Fluctuation phenomena, random processes, noise, and Brownian motion / 89.70.Cf – Entropy and other measures of information / 89.65.Gh – Economics; econophysics, financial markets, business and management
© 2021 EPLA
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