Volume 133, Number 6, March 2021
|Number of page(s)||7|
|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
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.