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Controversy in financial chaos research and nonlinear dynamics: A short literature review

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  • Vogl, Markus

Abstract

In this study, we apply a bibliometric analysis paired with a subsequent snowball sampling procedure. Moreover, we display a full citation network analysis, outlining the most relevant publications and contributions, defining relevant measures and show the interconnectivities and gaps within the existing research. Second, we will present a controversy within financial chaos literature, namely, whether financial dataset dynamics are chaotic or stochastic in nature and state empirical insights derived from the sampled literature. In addition, we show the interconnections between chaoticity, Hurst exponents, multifractality, scaling, long memory and market efficiency. Finally, we conclude our findings and discuss critically future avenues of research.

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  • Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:chsofr:v:162:y:2022:i:c:s0960077922006543
    DOI: 10.1016/j.chaos.2022.112444
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    Cited by:

    1. Ren, Jinfu & Liu, Yang & Liu, Jiming, 2023. "Chaotic behavior learning via information tracking," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    2. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    3. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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    More about this item

    Keywords

    Nonlinear dynamics; Chaos; Financial chaos; Literature review; Financial markets; Quantitative modelling;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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