Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency
By Luciano Zunino, Massimiliano Zanin, Benjamin Miranda Tabak, D. Pérez, Osvaldo Anibal Rosso. 2010
204 citations recorded by the source corpus.
The complexity-entropy causality plane has been recently introduced as a powerful tool for discriminating Gaussian from non-Gaussian process and different degrees of correlations [O.A. Rosso, H.A. Larrondo, M.T. Martin, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102]. We propose to use this representation space to distinguish the stage of stock market development. Our empirical results demonstrate that this statistical physics approach is useful, allowing a more refined classification of stock market dynamics.
Subfields: Economics and Econometrics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/0167a49d38373a19ed36158eeccaf7071a3a62e9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Aurelio Fernández Bariviera
- Ladislav Kristoufek
- Miloslav S. Vosvrda
- Luciano Zunino
- Osvaldo Anibal Rosso
- F. Serinaldi
- Marcelo R. Naiouf
- Mar'ia Jos'e Basgall
In Statistical and Nonlinear Physics
- Aurelio Fernández Bariviera
- Miloslav S. Vosvrda
- F. Serinaldi
- Luciano Zunino
- Osvaldo Anibal Rosso
- Ladislav Kristoufek
- Tetsuya Takaishi
- Paraskevi Katsiampa
Citations in the corpus
- Some stylized facts of the Bitcoin market (2017, background): “[59] shows that this innovative approach could be used to rank stock markets according to their stage of development.”
- Complexity–entropy analysis of daily stream flow time series in the continental United States (2014, methodology): “…detecting noise-induced temporal correlations in stochastic resonance phenomena (Rosso and Masoller 2009a, b), characterizing financial time series (Zunino et al. 2009, 2010b, 2011, 2012a), quantifying the randomness of chaotic pseudo-random number generators (De Micco et al. 2009), characterizing…”
- Commodity futures and market efficiency (2013, methodology): “Zunino et al. (2010) utilize the complexity–entropy causality plane to rank stock market indices to show that the emerging markets are less efficient than the developed ones, as one would expect.”