Review Article
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Year 2025, Volume: 7 Issue: 1, 70 - 77, 31.03.2025
https://doi.org/10.51537/chaos.1634673

Abstract

References

  • Altan, A., S. Karasu, and S. Bekiros, 2019 Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques. Chaos, Solitons & Fractals 126: 325–336.
  • Bariviera, A., M. Guercio, L. B. Martinez, and A. Rosso, 2015 The (in) visible hand in the Libor market: an information theory approach. The European Physical Journal B 88: 1–9.
  • Bella, G. and P. Mattana, 2020 Chaos control in presence of financial bubbles. Economics Letters 193.
  • Belle, A. and Y. Zhao, 2022 A Checklist-Based Approach to Assess the Abstracts of Reviews Self-Identifying as Systematic Reviews. 29th Asia-Pacific Software Engineering Conference (APSEC) pp. 502–506.
  • BenSaïda, H., A.and Litimi, 2013 High level chaos in the exchange and index markets. Chaos,Solitons & Fractals 54: 90–95.
  • Bianchi, S. and M. Frezza, 2017 Fractal stock markets: International evidence of dynamical (in)efficiency. Chaos: An Interdisciplinary Journal of Nonlinear Science 7.
  • Bowden, M., 2012 Information contagion within small worlds and changes in kurtosis and volatility in financial prices. Journal of Macroeconomics 2: 553–566.
  • Cavalli, F., A. K. Naimzada, N. Pecora, and M. Pireddu, 2018 Agents’ beliefs and economic regimes polarization in interacting markets. Chaos: An Interdisciplinary Journal of Nonlinear Science 5.
  • Cheriyan, V. and A. J. Kleywegt, 2016 A dynamical systems model of price bubbles and cycles. Quantitative Finance 2: 309–336.
  • Dercole, F. and D. Radi, 2020 Does the “uptick rule” stabilize the stock market? insights from adaptive rational equilibrium dynamics. Chaos, Solitons & Fractals 130: 109426.
  • Ferdinansyah, A. and B. Purwandari, 2021 Challenges in combining agile development and cmmi: A systematic literature review. ICSCA ’21: Proceedings of the 2021 10th International Conference on Software and Computer Applications pp. 63–69.
  • Frezza, M., 2018 A fractal-based approach for modeling stock price variations. Chaos: An Interdisciplinary Journal of Nonlinear Science 9.
  • Ge, X. L. and A. J. Lin, 2022 Kernel change point detection based on convergent cross mapping. Communications in Nonlinear Science and Numerical Simulation 109.
  • Ghosh, B., S. Papathanasiou, V. Dar, and D. Kenourgios, 2022 Deconstruction of the green bubble during covid-19 international evidence. Sustainability 14: 3466.
  • Gilmore, C. G., 2001 An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory. Global Finance Journal 1: 139–151.
  • Gu, E.-G., 2020 On the Price Dynamics of a Two-Dimensional Financial Market Model with Entry Levels. Complexity pp. 1– 23.
  • Hajirahimi, Z., M. Khashei, and S. Etemadi, 2022 A novel class of reliability-based parallel hybridization (rph) models for time series forecasting. Chaos, Solitons & Fractals 156: 111880.
  • Kim, D., S. Y. Choi, and J. H. Yoon, 2021 Pricing of vulnerable options under hybrid stochastic and local volatility. Chaos, Solitons & Fractals .
  • Kozłowska, M., M. Denys, M. Wili ´ nski, G. Link, T. Gubiec, et al., 2016 Dynamic bifurcations on financial markets. Chaos, Solitons & Fractals C: 126–142.
  • Lahmiri, S. and S. Bekiros, 2017 Disturbances and complexity in volatility time series. Chaos, Solitons & Fractals C: 38–42.
  • Lee, M.-K., S.-J. Yang, and J.-H. Kim, 2016 A closed form solution for vulnerable options with Heston’s stochastic volatility. Chaos, Solitons & Fractals C: 23–27.
  • Liu, X. and C. Jiang, 2020 Multi-scale features of volatility spillover networks: A case study of China’s energy stock market. Chaos: An Interdisciplinary Journal of Nonlinear Science 30.
  • Lu, X., 2020 A Financial Chaotic System Control Method Based on Intermittent Controller. Mathematical Problems in Engineering .
  • Ma, J., J. M. He, X. X. Liu, and C.Wang, 2019 Diversification and systemic risk in the banking system. Chaos, Solitons & Fractals C: 413–421.
  • Majewski, A., S. Ciliberti, and J. Bouchaud, 2019 Co-Existence of Trend and Value in Financial Markets: Estimating an Extended Chiarella Model. Journal of Economic Dynamics & Control .
  • McKenzie, M. D., 2001 Chaotic behavior in national stock market indices: New evidence from the close returns test. Global Finance Journal 1.
  • Nie, C. X., 2017 Dynamics of cluster structure in financial correlation matrix. Chaos, Solitons & Fractals 104: 835–840.
  • Nie, C. X., 2021 Dynamics of the price-volume information flow based on surrogate time series. Chaos: An Interdisciplinary Journal of Nonlinear Science 1.
  • Omane-Adjepong, M. and I. P. Alagidede, 2020 High-and lowlevel chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets. Chaos, Solitons & Fractals 132: 109563.
  • Ouandlous, A., J. T. Barkoulas, and Y. Alhaj-Yaseen, 2018 Persistence and discontinuity in the VIX Dynamics. Chaos, Solitons & Fractals 126: 333–344.
  • Ozkurt, C., 2024 Enhancing Financial Decision-Making: Predictive Modeling for Personal Loan Eligibility with Gradient Boosting, XGBoost, and AdaBoost. Information Technlogy in Economics & Business 1: 7–13.
  • Page, M., J. E. McKenzie, P. M. Bossuyt, I. Boutron, T. C. Hoffmann, et al., 2021 The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. The Bmj .
  • Paschou, T., M. Rapaccini, F. Adrodegari, and N. Saccani, 2020 Digital servitization in manufacturing: A systematic literature review and research agenda. Industrial Marketing Management pp. 278–292.
  • Samanidou, E., E. Zschischang, D. Stauffer, and T. Lux, 2007 Agent based model of financil markets. Reports on Progress in Physics 3: 409.
  • Sanjuan, M. A. F., 2021 Unpredictability uncertainty and fractal structures in physics. Chaos Theory and Appications 3: 43–46.
  • Serletis, A. and A. A. Rosenberg, 2009 Mean reversion in the us stock market. Chaos, Solitons & Fractals 40: 2007–2015.
  • Shynkevich, A., 2016 Predictability of equity returns during a financial crisis. Applied Economics Letter 17: 1201–1205.
  • Silva, T. C., S. R. S. de Souza, and B. M. Tabak, 2016 Structure and Dynamics of the Global Financial Network. Chaos Solitons & Fractal pp. 218–234.
  • Silver, S. D., M. Raseta, and A. Bazarova, 2022 Dynamics of Phase Transitions in Expectations for Financial Markets: An Agent- Based, Multicomponent Model. Journal of Behavioral Finance 1: 92–105.
  • Skjeltorp, J. A., 2000 Scaling in the Norwegian stock market. Physica A: Statistical Mechanics and its Applications 3: 486–528.
  • Todea, A., 2016 Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets. Chaos, Solitons & Fractals C: 208–215.
  • Tsakonas, S., M. M. L. Hanias, and L. Zachilas, 2022 Application of the moving Lyapunov exponent to the S&P 500 index to predict major declines. Journal of Risk 5.
  • Tsionas, M. G. and P. G. Michaelides, 2017 Neglected chaos in international stock markets: Bayesian analysis of the joint returnvolatility dynamical system. Physica A: Statistical Mechanics and its Applications pp. 95–107.
  • Vamvakaris, M. D., A. A. Pantelous, and K. M. Zuev, 2018 Time series analysis of S&P 500 index: A horizontal visibility graph approach. Physica A: Statistical Mechanics and its Applications pp. 41–51.
  • Wang, H., J.Wang, and G.Wang, 2018 Nonlinear continuous fluctuation intensity financial dynamics and complexity behavior. Chaos: An Interdisciplinary Journal of Nonlinear Science 8: 95– 107.
  • Wang, R., X. Hui, and X. Zhang, 2014 Analysis of Multiple Structural Changes in Financial Contagion Based on the Largest Lyapunov Exponents. Mathematical Problems in Engineering pp. 1–7.
  • Yin, T. and Y. Wang, 2019 Predicting the Price of WTI Crude Oil Using ANN and Chaos. Sustainability 21: 208–215.
  • Yuan, G. N., D. Ding, J. Q. Duan,W. G. Lu, and F. Y.Wu, 2022 Total value adjustment of Bermudan option valuation under pure jump Levy fluctuations. Chaos: An Interdisciplinary Journal of Nonlinear Science 2: 95–107.

Chaos Theory and Financial Markets: A Systematic Review of Crisis and Bubbles

Year 2025, Volume: 7 Issue: 1, 70 - 77, 31.03.2025
https://doi.org/10.51537/chaos.1634673

Abstract

Financial markets have been characterized by various financial crises and unpredictable fluctuations and price movements. While traditional finance theories, which assume that financial markets are composed of rational participants, fail to explain the market dynamics that cause crises, chaos theory provides a powerful framework to make sense of the unpredictable, deterministic nature of markets. Chaos theory claims that market fluctuations are not random but have a specific mathematical pattern.This study presents a systematic literature review addressing the relationship between chaos theory and financial crises and speculative bubbles. By analyzing articles from the Web of Science database, its relationship with crisis and bubble dynamics, and the main methodological approaches. This study explores the effectiveness of chaos theory in understanding financial instability in the context of financial crises and bubbles by examining the research questions identified for the application of chaos theory in finance through Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology and keyword analysis.

Ethical Statement

I, Oylum Şehvez Ergüzel, hereby declare that this manuscript titled “Chaos Theory and Financial Markets: A Systematic Review of Crisis and Bubbles” is an original work and has not been published or submitted for publication elsewhere. This study has been conducted in accordance with ethical research standards. The research does not involve any human participants, animals, or sensitive data requiring ethical approval. There are no conflicts of interest related to this research. All data sources have been properly cited, and due acknowledgment has been given to all contributors. I confirm that the manuscript complies with the ethical standards required by “Chaos Theory and Applications” and that all necessary permissions have been obtained. Oylum Şehvez Ergüzel Sakarya University 06.02.2025

References

  • Altan, A., S. Karasu, and S. Bekiros, 2019 Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques. Chaos, Solitons & Fractals 126: 325–336.
  • Bariviera, A., M. Guercio, L. B. Martinez, and A. Rosso, 2015 The (in) visible hand in the Libor market: an information theory approach. The European Physical Journal B 88: 1–9.
  • Bella, G. and P. Mattana, 2020 Chaos control in presence of financial bubbles. Economics Letters 193.
  • Belle, A. and Y. Zhao, 2022 A Checklist-Based Approach to Assess the Abstracts of Reviews Self-Identifying as Systematic Reviews. 29th Asia-Pacific Software Engineering Conference (APSEC) pp. 502–506.
  • BenSaïda, H., A.and Litimi, 2013 High level chaos in the exchange and index markets. Chaos,Solitons & Fractals 54: 90–95.
  • Bianchi, S. and M. Frezza, 2017 Fractal stock markets: International evidence of dynamical (in)efficiency. Chaos: An Interdisciplinary Journal of Nonlinear Science 7.
  • Bowden, M., 2012 Information contagion within small worlds and changes in kurtosis and volatility in financial prices. Journal of Macroeconomics 2: 553–566.
  • Cavalli, F., A. K. Naimzada, N. Pecora, and M. Pireddu, 2018 Agents’ beliefs and economic regimes polarization in interacting markets. Chaos: An Interdisciplinary Journal of Nonlinear Science 5.
  • Cheriyan, V. and A. J. Kleywegt, 2016 A dynamical systems model of price bubbles and cycles. Quantitative Finance 2: 309–336.
  • Dercole, F. and D. Radi, 2020 Does the “uptick rule” stabilize the stock market? insights from adaptive rational equilibrium dynamics. Chaos, Solitons & Fractals 130: 109426.
  • Ferdinansyah, A. and B. Purwandari, 2021 Challenges in combining agile development and cmmi: A systematic literature review. ICSCA ’21: Proceedings of the 2021 10th International Conference on Software and Computer Applications pp. 63–69.
  • Frezza, M., 2018 A fractal-based approach for modeling stock price variations. Chaos: An Interdisciplinary Journal of Nonlinear Science 9.
  • Ge, X. L. and A. J. Lin, 2022 Kernel change point detection based on convergent cross mapping. Communications in Nonlinear Science and Numerical Simulation 109.
  • Ghosh, B., S. Papathanasiou, V. Dar, and D. Kenourgios, 2022 Deconstruction of the green bubble during covid-19 international evidence. Sustainability 14: 3466.
  • Gilmore, C. G., 2001 An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory. Global Finance Journal 1: 139–151.
  • Gu, E.-G., 2020 On the Price Dynamics of a Two-Dimensional Financial Market Model with Entry Levels. Complexity pp. 1– 23.
  • Hajirahimi, Z., M. Khashei, and S. Etemadi, 2022 A novel class of reliability-based parallel hybridization (rph) models for time series forecasting. Chaos, Solitons & Fractals 156: 111880.
  • Kim, D., S. Y. Choi, and J. H. Yoon, 2021 Pricing of vulnerable options under hybrid stochastic and local volatility. Chaos, Solitons & Fractals .
  • Kozłowska, M., M. Denys, M. Wili ´ nski, G. Link, T. Gubiec, et al., 2016 Dynamic bifurcations on financial markets. Chaos, Solitons & Fractals C: 126–142.
  • Lahmiri, S. and S. Bekiros, 2017 Disturbances and complexity in volatility time series. Chaos, Solitons & Fractals C: 38–42.
  • Lee, M.-K., S.-J. Yang, and J.-H. Kim, 2016 A closed form solution for vulnerable options with Heston’s stochastic volatility. Chaos, Solitons & Fractals C: 23–27.
  • Liu, X. and C. Jiang, 2020 Multi-scale features of volatility spillover networks: A case study of China’s energy stock market. Chaos: An Interdisciplinary Journal of Nonlinear Science 30.
  • Lu, X., 2020 A Financial Chaotic System Control Method Based on Intermittent Controller. Mathematical Problems in Engineering .
  • Ma, J., J. M. He, X. X. Liu, and C.Wang, 2019 Diversification and systemic risk in the banking system. Chaos, Solitons & Fractals C: 413–421.
  • Majewski, A., S. Ciliberti, and J. Bouchaud, 2019 Co-Existence of Trend and Value in Financial Markets: Estimating an Extended Chiarella Model. Journal of Economic Dynamics & Control .
  • McKenzie, M. D., 2001 Chaotic behavior in national stock market indices: New evidence from the close returns test. Global Finance Journal 1.
  • Nie, C. X., 2017 Dynamics of cluster structure in financial correlation matrix. Chaos, Solitons & Fractals 104: 835–840.
  • Nie, C. X., 2021 Dynamics of the price-volume information flow based on surrogate time series. Chaos: An Interdisciplinary Journal of Nonlinear Science 1.
  • Omane-Adjepong, M. and I. P. Alagidede, 2020 High-and lowlevel chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets. Chaos, Solitons & Fractals 132: 109563.
  • Ouandlous, A., J. T. Barkoulas, and Y. Alhaj-Yaseen, 2018 Persistence and discontinuity in the VIX Dynamics. Chaos, Solitons & Fractals 126: 333–344.
  • Ozkurt, C., 2024 Enhancing Financial Decision-Making: Predictive Modeling for Personal Loan Eligibility with Gradient Boosting, XGBoost, and AdaBoost. Information Technlogy in Economics & Business 1: 7–13.
  • Page, M., J. E. McKenzie, P. M. Bossuyt, I. Boutron, T. C. Hoffmann, et al., 2021 The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. The Bmj .
  • Paschou, T., M. Rapaccini, F. Adrodegari, and N. Saccani, 2020 Digital servitization in manufacturing: A systematic literature review and research agenda. Industrial Marketing Management pp. 278–292.
  • Samanidou, E., E. Zschischang, D. Stauffer, and T. Lux, 2007 Agent based model of financil markets. Reports on Progress in Physics 3: 409.
  • Sanjuan, M. A. F., 2021 Unpredictability uncertainty and fractal structures in physics. Chaos Theory and Appications 3: 43–46.
  • Serletis, A. and A. A. Rosenberg, 2009 Mean reversion in the us stock market. Chaos, Solitons & Fractals 40: 2007–2015.
  • Shynkevich, A., 2016 Predictability of equity returns during a financial crisis. Applied Economics Letter 17: 1201–1205.
  • Silva, T. C., S. R. S. de Souza, and B. M. Tabak, 2016 Structure and Dynamics of the Global Financial Network. Chaos Solitons & Fractal pp. 218–234.
  • Silver, S. D., M. Raseta, and A. Bazarova, 2022 Dynamics of Phase Transitions in Expectations for Financial Markets: An Agent- Based, Multicomponent Model. Journal of Behavioral Finance 1: 92–105.
  • Skjeltorp, J. A., 2000 Scaling in the Norwegian stock market. Physica A: Statistical Mechanics and its Applications 3: 486–528.
  • Todea, A., 2016 Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets. Chaos, Solitons & Fractals C: 208–215.
  • Tsakonas, S., M. M. L. Hanias, and L. Zachilas, 2022 Application of the moving Lyapunov exponent to the S&P 500 index to predict major declines. Journal of Risk 5.
  • Tsionas, M. G. and P. G. Michaelides, 2017 Neglected chaos in international stock markets: Bayesian analysis of the joint returnvolatility dynamical system. Physica A: Statistical Mechanics and its Applications pp. 95–107.
  • Vamvakaris, M. D., A. A. Pantelous, and K. M. Zuev, 2018 Time series analysis of S&P 500 index: A horizontal visibility graph approach. Physica A: Statistical Mechanics and its Applications pp. 41–51.
  • Wang, H., J.Wang, and G.Wang, 2018 Nonlinear continuous fluctuation intensity financial dynamics and complexity behavior. Chaos: An Interdisciplinary Journal of Nonlinear Science 8: 95– 107.
  • Wang, R., X. Hui, and X. Zhang, 2014 Analysis of Multiple Structural Changes in Financial Contagion Based on the Largest Lyapunov Exponents. Mathematical Problems in Engineering pp. 1–7.
  • Yin, T. and Y. Wang, 2019 Predicting the Price of WTI Crude Oil Using ANN and Chaos. Sustainability 21: 208–215.
  • Yuan, G. N., D. Ding, J. Q. Duan,W. G. Lu, and F. Y.Wu, 2022 Total value adjustment of Bermudan option valuation under pure jump Levy fluctuations. Chaos: An Interdisciplinary Journal of Nonlinear Science 2: 95–107.
There are 48 citations in total.

Details

Primary Language English
Subjects Finance
Journal Section Review Article
Authors

Oylum Şehvez Ergüzel 0000-0001-9266-8267

Publication Date March 31, 2025
Submission Date February 6, 2025
Acceptance Date March 7, 2025
Published in Issue Year 2025 Volume: 7 Issue: 1

Cite

APA Ergüzel, O. Ş. (2025). Chaos Theory and Financial Markets: A Systematic Review of Crisis and Bubbles. Chaos Theory and Applications, 7(1), 70-77. https://doi.org/10.51537/chaos.1634673

Chaos Theory and Applications in Applied Sciences and Engineering: An interdisciplinary journal of nonlinear science 23830 28903   

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