IDEAS home Printed from https://ideas.repec.org/a/pes/ieroec/v13y2022i3p699-743.html
   My bibliography  Save this article

Multifrequency-based non-linear approach to analyzing implied volatility transmission across global financial markets

Author

Listed:
  • Ebenezer Boateng

    (University of Cape Coast, Ghana)

  • Emmanuel Asafo-Adjei

    (University of Cape Coast, Ghana)

  • John Gartchie Gatsi

    (University of Cape Coast, Ghana)

  • ªtefan Cristian Gherghina

    (Bucharest University of Economic Studies, Romania)

  • Liliana Nicoleta Simionescu

    (Bucharest University of Economic Studies, Romania)

Abstract

Research background: The contagious impact of the COVID-19 pandemic has heightened financial market's volatility, nonlinearity, asymmetric and nonstationary dynamics. Hence, the existing relationship among financial assets may have been altered. Moreover, the level of investor risk aversion and market opportunities could also alter in the pandemic. Predictably, investors in the heat of the moment are concerned about minimizing losses. In order to determine the level of hedge risks between implied volatilities in the COVID-19 pandemic through information flow, it is required to take into account the increased vagueness of economic projections as well as the increased uncertainty in asset values as a result of the pandemic. Purpose of the article: The study aims to examine the transmission of information between the VIX-implied volatility index for S&P 500 and fifteen other implied volatility indices in the COVID-19 pandemic. Methods: We relied on daily changes in the VIX and fifteen other implied volatility indices from commodities, currencies, and stocks. The study employed the improved complete ensemble empirical mode decomposition with adaptive noise which is in line with the heterogeneous expectations of market participants to denoise the data and extract intrinsic mode functions (IMFs). Subsequently, we clustered the IMFs based on common features into high, low, and medium frequencies. The analysis was carried out using Rényi transfer entropy (RTE), which allowed for the evaluation of both linear and non-linear, as well as varied distributions of the market dynamics. Findings & value added: Findings from the RTE revealed a bi-directional flow of negative information amid the VIX and each of the volatility indices, particularly in the long term. We found this behavior of the markets to be consistent at varying levels of investors' risk aversion. The findings help investors with their portfolio strategies in the time of the pandemic, which has resulted in fluctuating levels of risk aversion. Our findings characterize global financial markets to be “non-linear heterogeneous evolutionary systems”. The results also lend support to the emerging delayed volatility of market competitiveness and external shocks hypothesis.

Suggested Citation

  • Ebenezer Boateng & Emmanuel Asafo-Adjei & John Gartchie Gatsi & ªtefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2022. "Multifrequency-based non-linear approach to analyzing implied volatility transmission across global financial markets," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 699-743, September.
  • Handle: RePEc:pes:ieroec:v:13:y:2022:i:3:p:699-743
    DOI: 10.24136/oc.2022.021
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.24136/oc.2022.021
    Download Restriction: no

    File URL: https://libkey.io/10.24136/oc.2022.021?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
    ---><---

    References listed on IDEAS

    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    2. Gallegati, Marco, 2012. "A wavelet-based approach to test for financial market contagion," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3491-3497.
    3. Dutta, Anupam & Nikkinen, Jussi & Rothovius, Timo, 2017. "Impact of oil price uncertainty on Middle East and African stock markets," Energy, Elsevier, vol. 123(C), pages 189-197.
    4. Espinosa-Méndez, Christian & Arias, Jose, 2021. "COVID-19 effect on herding behaviour in European capital markets," Finance Research Letters, Elsevier, vol. 38(C).
    5. Boateng, Ebenezer & Adam, Anokye M. & Junior, Peterson Owusu, 2021. "Modelling the heterogeneous relationship between the crude oil implied volatility index and African stocks in the coronavirus pandemic," Resources Policy, Elsevier, vol. 74(C).
    6. Ahmed Bossman & Paulo Jorge Silveira Ferreira, 2021. "Information Flow from COVID-19 Pandemic to Islamic and Conventional Equities: An ICEEMDAN-Induced Transfer Entropy Analysis," Complexity, Hindawi, vol. 2021, pages 1-20, December.
    7. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    8. 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).
    9. Siong Hook Law & Muzafar Shah Habibullah, 2009. "The Determinants Of Financial Development: Institutions, Openness And Financial Liberalisation," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 45-58, March.
    10. Samuel Kwaku Agyei & Anokye Mohammed Adam & Ahmed Bossman & Oliver Asiamah & Peterson Owusu Junior & Roberta Asafo-Adjei & Emmanuel Asafo-Adjei, 2022. "Does volatility in cryptocurrencies drive the interconnectedness between the cryptocurrencies market? Insights from wavelets," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2061682-206, December.
    11. Tissaoui, Kais & Zaghdoudi, Taha, 2021. "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 481-492.
    12. Yue Peng & Wing Ng, 2012. "Analysing financial contagion and asymmetric market dependence with volatility indices via copulas," Annals of Finance, Springer, vol. 8(1), pages 49-74, February.
    13. Bui, Tung Duy & Bui, Hoai Thi Mai, 2020. "Threshold effect of economic openness on bank risk-taking: Evidence from emerging markets," Economic Modelling, Elsevier, vol. 91(C), pages 790-803.
    14. Katarina Valaskova & Tomas Kliestik & Dominika Gajdosikova, 2021. "Distinctive determinants of financial indebtedness: evidence from Slovak and Czech enterprises," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(3), pages 639-659, September.
    15. Boateng, Ebenezer & Asafo-Adjei, Emmanuel & Addison, Alex & Quaicoe, Serebour & Yusuf, Mawusi Ayisat & Abeka, Mac Junior & Adam, Anokye M., 2022. "Interconnectedness among commodities, the real sector of Ghana and external shocks," Resources Policy, Elsevier, vol. 75(C).
    16. Badshah, Ihsan & Bekiros, Stelios & Lucey, Brian M. & Uddin, Gazi Salah, 2018. "Asymmetric linkages among the fear index and emerging market volatility indices," Emerging Markets Review, Elsevier, vol. 37(C), pages 17-31.
    17. Zynobia Barson & Peterson Owusu Junior & Anokye M. Adam & Emmanuel Asafo-Adjei & Mariya Gubareva, 2022. "Connectedness between Gold and Cryptocurrencies in COVID-19 Pandemic: A Frequency-Dependent Asymmetric and Causality Analysis," Complexity, Hindawi, vol. 2022, pages 1-17, April.
    18. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 1-13.
    19. Emmanuel Asafo-Adjei & Siaw Frimpong & Peterson Owusu Junior & Anokye Mohammed Adam & Ebenezer Boateng & Robert Ofori Abosompim & A. Dionisio, 2022. "Multi-Frequency Information Flows between Global Commodities and Uncertainties: Evidence from COVID-19 Pandemic," Complexity, Hindawi, vol. 2022, pages 1-32, May.
    20. Ihsan U. Badshah, 2018. "Volatility Spillover from the Fear Index to Developed and Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(1), pages 27-40, January.
    21. Mehmet Balcilar & Riza Demirer, 2015. "Effect of Global Shocks and Volatility on Herd Behavior in an Emerging Market: Evidence from Borsa Istanbul," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(1), pages 140-159, January.
    22. Anokye M. Adam & Kwabena Kyei & Simiso Moyo & Ryan Gill & Emmanuel N. Gyamfi, 2022. "Similarities in Southern African Development Community (SADC) Exchange Rate Markets Structure: Evidence from the Ensemble Empirical Mode Decomposition," Journal of African Business, Taylor & Francis Journals, vol. 23(2), pages 516-530, April.
    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. Thobekile Qabhobho, 2023. "Assessing the Asymmetric Effect of Local Realized Exchange Rate Volatility and Implied Volatilities in Energy Market on Exchange Rate Returns in BRICS," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 231-239, March.
    2. Bossman, Ahmed & Agyei, Samuel Kwaku, 2022. "Interdependence structure of global commodity classes and African equity markets: A vector wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
    3. Boateng, Ebenezer & Adam, Anokye M. & Junior, Peterson Owusu, 2021. "Modelling the heterogeneous relationship between the crude oil implied volatility index and African stocks in the coronavirus pandemic," Resources Policy, Elsevier, vol. 74(C).
    4. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    5. Tian, Meiyu & Li, Wanyang & Wen, Fenghua, 2021. "The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    6. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Dynamics and determinants of spillovers across the option-implied volatilities of US equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 257-264.
    7. Bhuiyan, Rubaiyat Ahsan & Husain, Afzol & Zhang, Changyong, 2021. "A wavelet approach for causal relationship between bitcoin and conventional asset classes," Resources Policy, Elsevier, vol. 71(C).
    8. Thobekile Qabhobho & Anokye M. Adam & Anthony Adu-Asare Idun & Emmanuel Asafo-Adjei & Ebenezer Boateng, 2023. "Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 272-283, March.
    9. Saiti, Buerhan & Bacha, Obiyathulla & Masih, Mansur, 2014. "Is the global leadership of the US financial market over other financial markets shaken by 2007-2009 financial crisis? Evidence from Wavelet Analysis," MPRA Paper 57064, University Library of Munich, Germany.
    10. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
    11. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    12. Ghazani, Majid Mirzaee & Khosravi, Reza & Caporin, Massimiliano, 2023. "Analyzing interconnection among selected commodities in the 2008 global financial crisis and the COVID-19 pandemic," Resources Policy, Elsevier, vol. 80(C).
    13. Wahbeeah Mohti & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2019. "Contagion of the Subprime Financial Crisis on Frontier Stock Markets: A Copula Analysis," Economies, MDPI, vol. 7(1), pages 1-14, February.
    14. Mohammed Mizanur Rahman & Munni Begum & Badar Nadeem Ashraf & Md. Abdul Kaium Masud, 2020. "Does Trade Openness Affect Bank Risk-Taking Behavior? Evidence from BRICS Countries," Economies, MDPI, vol. 8(3), pages 1-30, September.
    15. Lee, Hsiu-Chuan & Lee, Yun-Huan & Nguyen, Cuong, 2023. "Tail comovements of implied volatility indices and global index futures returns predictability," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    16. Chen, Chun-Da & Chiang, Shu-Mei & Huang, Tze-Chin, 2020. "The contagion effects of volatility indices across the U.S. and Europe," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    17. Mohammad Sharik Essa & Evangelos Giouvris, 2020. "Oil Price, Oil Price Implied Volatility (OVX) and Illiquidity Premiums in the US: (A)symmetry and the Impact of Macroeconomic Factors," JRFM, MDPI, vol. 13(4), pages 1-40, April.
    18. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    19. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    20. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.

    More about this item

    Keywords

    shocks transmission; information flow; Rényi transfer entropy; multi-scale; market conditions;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G01 - Financial Economics - - General - - - Financial Crises
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    Statistics

    Access and download statistics

    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:pes:ieroec:v:13:y:2022:i:3:p:699-743. 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: Adam P. Balcerzak (email available below). General contact details of provider: https://edirc.repec.org/data/ibgtopl.html .

    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.