IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v202y2022icp480-499.html
   My bibliography  Save this article

Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction

Author

Listed:
  • Alves, P.R.L.

Abstract

From a methodology in the reconstruction scheme, applicable to chaotic time series of economic indices, this paper presents an analysis of the underlying dynamics of stock markets of North America, Europe and Asia. The same global fit model and reconstruction parameters—employed to study the time evolution of S&P 500, NASDAQ Composite, IBEX 35, EURONEXT 100, Nikkei 225 and SSE Composite Index—led a convenient simplification in the analysis. The tools chosen to analyse the time dependence of the level of chaos concerning weeks of economic activity were scatter plots, histograms and sample Spearman correlation coefficients. The results permit to evaluate the impact of the pandemic in the underlying dynamics of different stock markets and to compare them to one another.

Suggested Citation

  • Alves, P.R.L., 2022. "Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 480-499.
    • Handle: RePEc:eee:matcom:v:202:y:2022:i:c:p:480-499
    DOI: 10.1016/j.matcom.2022.07.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475422003287
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2022.07.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    2. Zribi, Wissal & Boufateh, Talel, 2020. "Asymmetric CEO confidence and CSR: A nonlinear panel ARDL-PMG approach," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    3. Lahmiri, Salim & Bekiros, Stelios, 2020. "Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Aliyev, Fuzuli & Ajayi, Richard & Gasim, Nijat, 2020. "Modelling asymmetric market volatility with univariate GARCH models: Evidence from Nasdaq-100," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    5. Urom, Christian & Ndubuisi, Gideon & Ozor, Jude, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, Elsevier, vol. 165(C), pages 51-66.
    6. Padhan, Hemachandra & Sahu, Santosh Kumar & Dash, Umakant, 2021. "Non-linear analysis of international reserve, trade and trilemma in India," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    7. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    8. Contreras G., Mauricio & Peña, Juan Pablo & Aros, Rodrigo, 2021. "Second class constraints and the consistency of optimal control theory in phase space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    9. Alves, P.R.L. & Duarte, L.G.S. & da Mota, L.A.C.P., 2018. "Detecting chaos and predicting in Dow Jones Index," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 232-238.
    10. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    11. Alves, P.R.L. & Duarte, L.G.S. & da Mota, L.A.C.P., 2017. "A new characterization of chaos from a time series," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 323-326.
    12. Lahmiri, Salim & Bekiros, Stelios, 2020. "The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    13. Panagiotou, Dimitrios, 2021. "Asymmetric price responses of the US pork retail prices to farm and wholesale price shocks: A nonlinear ARDL approach," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    14. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    15. Alves, P.R.L., 2020. "Dynamic characteristic of Bitcoin cryptocurrency in the reconstruction scheme," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Stefan Armeanu & Stefan Cristian Gherghina & Jean Vasile Andrei & Camelia Catalina Joldes, 2023. "Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets," Energy & Environment, , vol. 34(5), pages 1433-1470, August.
    2. Ben Khelifa, Soumaya & Guesmi, Khaled & Urom, Christian, 2021. "Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    3. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Gil-Alana, Luis Alberiko, 2022. "The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    4. Lahmiri, Salim & Bekiros, Stelios, 2020. "Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    6. Akhtaruzzaman, Md & Boubaker, Sabri & Sensoy, Ahmet, 2021. "Financial contagion during COVID–19 crisis," Finance Research Letters, Elsevier, vol. 38(C).
    7. Radosław Puka & Bartosz Łamasz & Marek Michalski, 2021. "Using Artificial Neural Networks to Support the Decision-Making Process of Buying Call Options Considering Risk Appetite," Energies, MDPI, vol. 14(24), pages 1-24, December.
    8. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2020. "Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis," IJERPH, MDPI, vol. 17(18), pages 1-35, September.
    9. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    10. Kumeka, Terver Theophilus & Uzoma-Nwosu, Damian Chidozie & David-Wayas, Maria Onyinye, 2022. "The effects of COVID-19 on the interrelationship among oil prices, stock prices and exchange rates in selected oil exporting economies," Resources Policy, Elsevier, vol. 77(C).
    11. Katarzyna Czech & Michał Wielechowski & Pavel Kotyza & Irena Benešová & Adriana Laputková, 2020. "Shaking Stability: COVID-19 Impact on the Visegrad Group Countries’ Financial Markets," Sustainability, MDPI, vol. 12(15), pages 1-19, August.
    12. Peng-Fei Dai & Xiong Xiong & Zhifeng Liu & Toan Luu Duc Huynh & Jianjun Sun, 2021. "Preventing crash in stock market: The role of economic policy uncertainty during COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
    13. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2021. "Oil price volatility in the context of Covid-19," International Economics, Elsevier, vol. 167(C), pages 39-49.
    14. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    15. Sanjay Kumar Rout & Hrushikesh Mallick, 2022. "Sovereign Bond Market Shock Spillover Over Different Maturities: A Journey from Normal to Covid-19 Period," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(4), pages 697-734, December.
    16. Hemrit, Wael & Benlagha, Noureddine, 2021. "Does renewable energy index respond to the pandemic uncertainty?," Renewable Energy, Elsevier, vol. 177(C), pages 336-347.
    17. Elgammal, Mohammed M. & Ahmed, Walid M.A. & Alshami, Abdullah, 2021. "Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    18. Elnahass, Marwa & Trinh, Vu Quang & Li, Teng, 2021. "Global banking stability in the shadow of Covid-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    19. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2021. "The Impact of Containment Measures and Monetary and Fiscal Responses on US Financial Markets during the Covid-19 Pandemic," CESifo Working Paper Series 9163, CESifo.
    20. Assaf, Ata & Mokni, Khaled & Youssef, Manel, 2023. "COVID-19 and information flow between cryptocurrencies, and conventional financial assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 73-81.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:202:y:2022:i:c:p:480-499. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.