Predictability: An Information-Theoretic Perspective

Darbellay, Georges A.

doi:10.1007/978-1-4612-1768-8_18

Cited by 26 publications

(23 citation statements)

References 2 publications

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“…This means that, even not rejecting the hypothesis that returns have no autocorrelation, it is possible that markets are not efficient if there is any other kind of dependence, and therefore, analysis of linear dependence is not sufficient (see, e.g., Darbellay, 1998a. Therefore, to study financial markets, it is necessary to follow general models that are capable of capturing global, and not only linear, dependence.…”

Section: A Survey On the Efficient Market Hypothesis: Some Empirimentioning

confidence: 99%

Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece

Ferreira

Dionísio

2014

Applied Financial Economics

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This article uses several tests to analyse serial dependence in financial data, trying to confirm the existence of some kind of nonlinear dependence in stock markets. In an attempt to provide a better explanation of the behaviour of stock markets, we used tests based on mutual information and detrended fluctuation analysis (DFA). Applying these tests to the series of stock market indexes of 10 countries, we concluded for the absence of linear autocorrelation. However, with other tests, we found nonlinear serial dependence that affects the rates of return. With DFA, we found out that most return rate series have long-range dependence, which appears to be more pronounced for Spain, Greece and Portugal. To confirm the inefficiency of those markets, based on our results, we should prove the existence of abnormal profits.

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Section: A Survey On the Efficient Market Hypothesis: Some Empirimentioning

confidence: 99%

Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece

Ferreira

Dionísio

2014

Applied Financial Economics

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“…To overcome this problem, there are essentially three different methods to estimate mutual information: histogram-based estimators, kernel-based estimators and parametric methods. 1 In order to minimize the bias that may occur, we will use the marginal equiquantization estimation process, proposed by Darbellay (1998).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

An econophysics approach to analyse uncertainty in financial markets: an application to the Portuguese stock market

2006

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In recent years there has been a closer interrelationship between several scientific areas trying to obtain a more realistic and rich explanation of the natural and social phenomena. Among these it should be emphasized the increasing interrelationship between physics and financial theory. In this field the analysis of uncertainty, which is crucial in financial analysis, can be made using measures of physics statistics and information theory, namely the Shannon entropy. One advantage of this approach is that the entropy is a more general measure than the variance, since it accounts for higher order moments of a probability distribution function. An empirical application was made using data collected from the Portuguese Stock Market.

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“…For the above calculations, we use 100 000 values. The algorithm for the estimation of the nonlinear predictability is described in Darbellay (1998) and Darbellay and Vajda (1999). The general idea behind this algorithm is the partitioning of R d into finite, non-intersecting subsets (cells) of R d whose sum is the whole R d .…”

Section: Applicationsmentioning

confidence: 99%

“…However, certain aspects of these systems may be less nonlinear than others and the nature of nonlinearity may not be always clear. The work here uses a newly developed method (Darbellay, 1998;Darbellay and Vajda, 1999) that provides insights into the nature of linearity and/or nonlinearity, thus allowing one to decide whether a specific process should be modeled with a linear or a nonlinear model. We apply this method to a time series from a known dynamical system (this series serves as our control example) and then to an observable from our climate system, which describes the transitions in the atmospheric circulation.…”

Section: Introductionmentioning

confidence: 99%

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Probing the linearity and nonlinearity in the transitions of the atmospheric circulation

Tsonis

2001

Nonlin. Processes Geophys.

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Abstract. In this paper, we apply the principles of information theory that relate to the definition of nonlinear predictability, which is a measure that describes both the linear and nonlinear components of a system. By comparing this measure to a measure of linear predictability, one can assess whether a given system has a strong nonlinear or a strong linear component. This provides insights as to whether the system should be modeled by a nonlinear model or by a linear model. We apply these ideas to a known dynamical system and to a time series that describe the transitions in atmospheric circulation.

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Predictability: An Information-Theoretic Perspective

Cited by 26 publications

References 2 publications

Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece

Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece

An econophysics approach to analyse uncertainty in financial markets: an application to the Portuguese stock market

Probing the linearity and nonlinearity in the transitions of the atmospheric circulation

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