Time and scale Hurst exponent analysis for financial markets

Matos, J. A. O.; Gama, S.; Ruskin, Heather J.; Sharkasi, Adel; Crane, Martin

doi:10.1016/j.physa.2008.01.060

Cited by 84 publications

(44 citation statements)

References 9 publications

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“…In this context, in their paper they present a new method based on the rescaled variance statistics which can be used efficiently to this end. Matos et al (2008) used a method of studying the Hurst exponent with time and scale dependency. This approach allowed them to recover the major events affecting worldwide markets and analyze the way those effects propagated through the different scales.…”

Section: International Journal Of Academic Research In Business and Smentioning

confidence: 99%

Applications of Chaos and Fractal Theory on Emerging Capital Markets

Oprean¹,

Tănăsescu²

2013

IJARBSS

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Abstract:The analysis of capital markets efficiency has attracted a considerable number of studies in empirical finance, but conflicting and inconclusive outcomes have been generated. The aim of this paper is to find any evidence that the selected emergent capital markets (eight emergent European and BRIC markets, namely Hungary, Romania, Estonia, Czech Republic, Brazil, Russia, India and China) abide by a particular evolution pattern (long range dependence) or the random walk hypothesis. In view of attaining the goal of the paper, we employed a methodology based on the interdisciplinary approach to the subject matter under investigation and applied the deterministic chaos and fractal theory. In this paper, the Hurst exponent calculated by the rescaled-range analysis is our measure of long range dependence in the series. We use a "rolling sample" approach to evaluate the Hurst exponent. The results suggest that this fractal exponent may be useful in assessing the stage of stock market inefficiency.

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Section: International Journal Of Academic Research In Business and Smentioning

confidence: 99%

Applications of Chaos and Fractal Theory on Emerging Capital Markets

Oprean¹,

Tănăsescu²

2013

IJARBSS

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“…Při malém počtu těchto statistik může jedno odlehlé pozorování celkový odhad výrazně ovlivnit. Opět podle doporučení ostatních autorů volíme nejvyšší použitou škálu υ max jako jednu čtrvtinu celkové délky časové řady (Peters, 1994;Grech, Mazur, 2004;Matos et al, 2008;Alvarez-Ramirez, Rodriguez, Echeverria, 2005;a Einstein, Wu, Gil, 2001). …”

Section: Parametry Metodunclassified

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

Krištoufek¹

2010

Politicka ekonomie

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“…However, studies have shown that the so called random phenomena exhibit some correlations which can be unmasked with some recently developed analytical tools. Occurrences such as earthquakes (Bak et al, 2002), landslides (Turcotte et al, 2002), rainfall, DNA (Peng et al, 1994), spot electricity, World Wide Web (Barabasi, 1999), forest fire (Turcotte et al, 2002) financial time series (Czarnecki et al, 2008;Grech and Mazur, 2004;Matos et al., 2008), fragmentation (Turcotte, 1997), fracture (Sornette, 2002), birth (Sornette, 2002), run off, daily temperature (Vjushin et al, 2002) have been shown not to be subject to pure chance but follow a power law.…”

Section: Introductionmentioning

confidence: 99%

Time series analysis of monthly rainfall in Nigeria with emphasis on self-organized criticality

Nnaji

2011

Jnl Sci Tech

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Monthly rainfall data of twenty-one years (1980 -2000) were analyzed for the six regions of Nigeria using the rescaled range (R/S) statistic, the standard fluctuation analysis (FA) and the detrended fluctuation analysis (DFA). The results indicated that the distribution of monthly rainfall has a Hurst exponent of 1 in the short term which is an evidence of self-organized criticality, and a Hurst exponent of about 0.5 in the long run which is an evidence of a random walk. The Hurst exponents decreased from around 1 for small window sizes and reached 0.5 after 36 months and then remained fairly constant. The R/S statistic was found to perform better than the FA and the linear DFA used in the analysis.

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Time and scale Hurst exponent analysis for financial markets

Cited by 84 publications

References 9 publications

Applications of Chaos and Fractal Theory on Emerging Capital Markets

Applications of Chaos and Fractal Theory on Emerging Capital Markets

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

Time series analysis of monthly rainfall in Nigeria with emphasis on self-organized criticality

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