IDEAS home Printed from https://ideas.repec.org/a/bas/econst/y2021i8p175-198.html
   My bibliography  Save this article

The Influence of Uncertainty on Market Efficiency: Evidence from Selected European Financial Markets

Author

Listed:
  • Mariya Paskaleva
  • Ani Stoykova

Abstract

The purpose of this study is to determine if the capital markets of fourteen European countries are efficient or not. Additionally, we examine the impact of VIX and GEPU returns on the market efficiency of the analyzed capital markets. We apply the Augmented Dickey-Fuller (ADF) test and Threshold GARCH (TGARCH) Model. The period under examination is 2003-2016. Our results show that the explored European markets are highly integrated, and in the context of the Efficient Market Hypothesis (EMH), a division along the line of the developed-developing market has been revealed. The Bulgarian capital market shows a strong degree of integration with the other explored economies in the conditions of EMH. The efficiency of the explored markets is improved by adding to the model VIX and GEPU returns. We prove that diversification can be achieved based on emerging markets of the EU Member States. Prolonged periods of low volatility can further reduce correlations, encouraging further risk-taking.

Suggested Citation

  • Mariya Paskaleva & Ani Stoykova, 2021. "The Influence of Uncertainty on Market Efficiency: Evidence from Selected European Financial Markets," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 175-198.
    • Handle: RePEc:bas:econst:y:2021:i:8:p:175-198
    as

    Download full text from publisher

    File URL: https://www.iki.bas.bg/Journals/EconomicStudies/2021/2021-8/9_Ani-Stoykova.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Victor Dragota & Dragos Stefan Oprea, 2014. "Informational Efficiency Tests on the Romanian Stock Market: A Review of the Literature," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(1), pages 015-028, June.
    2. Lei Ruan, 2018. "Research on Sustainable Development of the Stock Market Based on VIX Index," Sustainability, MDPI, vol. 10(11), pages 1-12, November.
    3. P. Corredor & E. Ferrer & R. Santamaria, 2015. "The Impact of Investor Sentiment on Stock Returns in Emerging Markets: The Case of Central European Markets," Eastern European Economics, Taylor & Francis Journals, vol. 53(4), pages 328-355, July.
    4. Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2018. "Learning from History: Volatility and Financial Crises," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2774-2805.
    5. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    6. Patrick Slovik, 2011. "Market uncertainty and market instability," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 430-435, Bank for International Settlements.
    7. Thomas C. Chiang, 2019. "Market Efficiency and News Dynamics: Evidence from International Equity Markets," Economies, MDPI, vol. 7(1), pages 1-17, February.
    8. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    9. BenSaïda, Ahmed & Litimi, Houda & Abdallah, Oussama, 2018. "Volatility spillover shifts in global financial markets," Economic Modelling, Elsevier, vol. 73(C), pages 343-353.
    10. Zdravkovski, Aleksandar, 2016. "Stock market integration and diversification possibilities during financial crises: Evidence from Balkan countries," MPRA Paper 72182, University Library of Munich, Germany.
    11. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    12. Daniel Stefan ARMEANU & Sorin-Iulian CIOACA, 2014. "Testing The Efficient Market Hypothesis On The Romanian Capital Market," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 8(1), pages 252-261, November.
    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. Ani Stoitsova-Stoykova, 2017. "Relationship Between Public Expectations and Financial Market Dynamics in South- East Europe Capital Markets," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 237-250, June.
    2. Mariya Paskaleva & Ani Stoitsova-Stoykova, 2017. "Linkages and Efficiency Between iTraxx Europe and Financial Market Dynamics in South-East Europe Capital Markets in Post-crisis Period," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 172-179.
    3. Wang, Bo & Xiao, Yang, 2023. "Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    4. Eva DEZSI & Ioan Alin NISTOR, 2016. "Can Deep Machine Learning Outsmart The Market? A Comparison Between Econometric Modelling And Long- Short Term Memory," Romanian Economic Business Review, Romanian-American University, vol. 11(4.1), pages 54-73, december.
    5. Alin Marius ANDRIEŞ & Iulian IHNATOV & Nicu SPRINCEAN, 2017. "Do Seasonal Anomalies Still Exist In Central And Eastern European Countries? A Conditional Variance Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 60-83, December.
    6. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    7. BenSaïda, Ahmed, 2019. "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, vol. 43(C), pages 78-95.
    8. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    9. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.
    10. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    11. Kumari, Jyoti, 2019. "Investor sentiment and stock market liquidity: Evidence from an emerging economy," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 166-180.
    12. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    13. B. De Backer, 2018. "Does financial market volatility influence the real economy?," Economic Review, National Bank of Belgium, issue iv, pages 107-124, december.
    14. Tsang, Andrew & Yiu, Matthew S. & Nguyen, Huy Toan, 2021. "Spillover across sovereign bond markets between the US and ASEAN4 economies," Journal of Asian Economics, Elsevier, vol. 76(C).
    15. Stefan Abrantes Costa & Pedro Manuel Nogueira Reis & Antonio Pedro Soares Pinto, 2020. "Subjective/ Behavioural Factors Influence the PSI 20 and IBEX 35," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(5), pages 13-27, October.
    16. Berna Aydogan, 2017. "Sentiment dynamics and volatility of international stock markets," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 7(3), pages 407-419, December.
    17. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    18. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    19. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    20. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:bas:econst:y:2021:i:8:p:175-198. 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: Diana Dimitrova (email available below). General contact details of provider: https://edirc.repec.org/data/ikbasbg.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.