Chaos in German stock returns — New evidence from the 0–1 test

Webel, Karsten

doi:10.1016/j.econlet.2011.12.110

Cited by 30 publications

(8 citation statements)

References 15 publications

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“…Algorithm. There are many approaches to detect chaos, but 0-1 test is one of the simplest and most effective ones, which was proposed by Gottwald and Melbourne [30] and also has already been successfully tested for various discrete or continuous systems, such as [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45].…”

Section: The 0-1 Testmentioning

confidence: 99%

0-1 Test for Chaos in a Fractional Order Financial System with Investment Incentive

Xin

2013

Abstract and Applied Analysis

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A new integer-order chaotic financial system is extended by introducing a simple investment incentive into a three-dimensional chaotic financial system. A four-dimensional fractional-order chaotic financial system is presented by bringing fractional calculus into the new integer-order financial system. By using weighted integral thought, the fractional order derivative's economics meaning is given. The 0-1 test algorithm and the improved Adams-Bashforth-Moulton predictor-corrector scheme are employed to detect numerically the chaos in the proposed fractional order financial system.

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Section: The 0-1 Testmentioning

confidence: 99%

0-1 Test for Chaos in a Fractional Order Financial System with Investment Incentive

Xin

2013

Abstract and Applied Analysis

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“…The stock market crash of 1987 provided further impetus to use of non-linear methods in financial research aimed at testing the validity of the random walk hypothesis (Lima 1998). In recent years, there has been spurt in studies which have refuted random walk and have documented nonlinear dynamics in a variety of financial return series (Ozer and Ertokatli, 2010;Mishra et al, 2011;Webel, 2012;Yilanci, 2012;Lim and Hooy, 2013;Madhavan 2014). However, existing literature provides mixed evidences on existence of non-linearity in financial return series.…”

Section: Nonlinearity In Financial Asset Marketsmentioning

confidence: 99%

Long Term Dynamics of Indian ADRs Market: The Case of Persistence and Irregular Cycles

Bora¹,

Kumar

2017

AFR

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The focus of this study is to understand the previously ignored return generating dynamics of American Depositary Receipts (ADR) markets. The main objective of this study is to investigate the nature of the return generating process of the Indian ADRs market. Specifically, the study addresses following interrelated research questions: Do returns series of Indian ADRs market exhibit random walk behavior or rather depict persistence and nonlinear dynamics? Is there any cyclicity in the returns series of Indian ADRs market? Rescaled Range (R/S) method on daily and weekly return series of Bank of the New York Mellon Indian ADR index (BKIN) from 2002 to 2016 has been applied to address the above questions. Empirical findings revealed that returns series of Indian ADRs market: (a) do not exhibit random walk behavior and rather depict both nonlinear behavior and persistence (long range dependence); (b) possess non-periodic cycles of 0.793, 2.38 and approximately 7 years. The findings can work as crucial inputs to forecasting, risk-management and market regulation processes. The knowledge of the average cycle length and persistence will enhance preparedness to handle the opportunities and risks at all levels in the market.

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“…This method requires, however, the reconstruction of a phase space which implies accepting certain biases so as to determine the immersion dimension, mean period and time of delay. Test 0-1 has recently been used to solve these inconveniences so as to determine chaos in financial series (Webel, 2012). The 0-1 test for chaos is based on a Euclidean extension instead of a phase space reconstruction.…”

Section: Introductionmentioning

confidence: 99%

An application of Rolling chaos 0-1 test on Stock Market

Espinoza

Gorigoitía

2020

BAS-UCHILE

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In this paper we apply a rolling 0-1 test for chaos on different stock market indices returns in the world, considering different time period windows to capture the effects of adding new information. A rolling sample is defined for each index and at the same time, wavelet denoising has been employed since approximately 1995 to the end of 2012. Empirical evidence of continuous chaotic behavior for all indices is found.

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Chaos in German stock returns — New evidence from the 0–1 test

Cited by 30 publications

References 15 publications

0-1 Test for Chaos in a Fractional Order Financial System with Investment Incentive

0-1 Test for Chaos in a Fractional Order Financial System with Investment Incentive

Long Term Dynamics of Indian ADRs Market: The Case of Persistence and Irregular Cycles

An application of Rolling chaos 0-1 test on Stock Market

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