L
Luciano Zunino
Researcher at National Scientific and Technical Research Council
Publications - 107
Citations - 3963
Luciano Zunino is an academic researcher from National Scientific and Technical Research Council. The author has contributed to research in topics: Fractional Brownian motion & Hurst exponent. The author has an hindex of 29, co-authored 103 publications receiving 3379 citations. Previous affiliations of Luciano Zunino include Spanish National Research Council & National University of La Plata.
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Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review
TL;DR: The theoretical foundations of the permutation entropy are analyzed, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.
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A multifractal approach for stock market inefficiency
Luciano Zunino,Benjamin Miranda Tabak,Benjamin Miranda Tabak,Alejandra Figliola,Darío G. Pérez,Mario Garavaglia,Osvaldo A. Rosso,Osvaldo A. Rosso +7 more
TL;DR: In this article, the authors evaluated the multifractality degree in a collection of developed and emerging stock market indices and found that higher multifractal degree is associated with a less developed market.
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Forbidden patterns, permutation entropy and stock market inefficiency
Luciano Zunino,Luciano Zunino,Massimiliano Zanin,Benjamin Miranda Tabak,Benjamin Miranda Tabak,Darío G. Pérez,Osvaldo A. Rosso,Osvaldo A. Rosso +7 more
TL;DR: In this article, the authors introduce two new quantifiers for the stock market inefficiency: the number of forbidden patterns and the normalized permutation entropy, which are model-independent measures and have more general applicability.
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Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency
Luciano Zunino,Luciano Zunino,Luciano Zunino,Massimiliano Zanin,Benjamin Miranda Tabak,Benjamin Miranda Tabak,Darío G. Pérez,Osvaldo A. Rosso,Osvaldo A. Rosso +8 more
TL;DR: This work proposes to use the complexity-entropy causality plane, a powerful tool for discriminating Gaussian from non-Gaussian process and different degrees of correlations, to distinguish the stage of stock market development.
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Distinguishing chaotic and stochastic dynamics from time series by using a multiscale symbolic approach
TL;DR: It is shown that the multiscale complexity-entropy causality plane is a useful representation space to identify the range of scales at which deterministic or noisy behaviors dominate the system's dynamics.