Add to ORKGThe 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. Martín, 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.Facultad de IngenieríaCentro de Investigaciones Óptica
International audienceThis paper focuses on the use of dynamical chaotic systems in Economics and Fi...
The Efficient Market Hypothesis has been the bedrock of quantitative capital market theory, and rese...
In this paper we introduce two new quantifiers for the stock market inefficiency: the number of forb...
The main purpose of this paper is efficiency analysis as well as its quantification in the case of e...
Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a ...
Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a ...
The thesis considers the problem of evaluating a degree of market efficiency. In a weak form of the ...
The existence of memory in financial time series has been extensively studied for several stock mark...
The aim of the contribution is to introduce a novel information plane, the causal-amplitude informat...
A methodology based on the algorithmic complexity theory has been applied to assess the relative eff...
Complex systems are ubiquitous. Their components, agents, live in an environment perceiving its chan...
We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Ef...
This paper investigates the degree of efficiency for the Moscow Stock Exchange. A market is called ...
We utilize long-term memory, fractal dimension and approximate entropy as input variables ...
This paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabili...
International audienceThis paper focuses on the use of dynamical chaotic systems in Economics and Fi...
The Efficient Market Hypothesis has been the bedrock of quantitative capital market theory, and rese...
In this paper we introduce two new quantifiers for the stock market inefficiency: the number of forb...
The main purpose of this paper is efficiency analysis as well as its quantification in the case of e...
Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a ...
Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a ...
The thesis considers the problem of evaluating a degree of market efficiency. In a weak form of the ...
The existence of memory in financial time series has been extensively studied for several stock mark...
The aim of the contribution is to introduce a novel information plane, the causal-amplitude informat...
A methodology based on the algorithmic complexity theory has been applied to assess the relative eff...
Complex systems are ubiquitous. Their components, agents, live in an environment perceiving its chan...
We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Ef...
This paper investigates the degree of efficiency for the Moscow Stock Exchange. A market is called ...
We utilize long-term memory, fractal dimension and approximate entropy as input variables ...
This paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabili...
International audienceThis paper focuses on the use of dynamical chaotic systems in Economics and Fi...
The Efficient Market Hypothesis has been the bedrock of quantitative capital market theory, and rese...
In this paper we introduce two new quantifiers for the stock market inefficiency: the number of forb...