IDEAS home Printed from https://ideas.repec.org/a/ist/ekoist/v0y2021i35p33-57.html
   My bibliography  Save this article

Comparative Analysis of the Volatility Structure of Cryptocurrencies

Author

Listed:
  • Fatih Kazova

    (Akdeniz Universitesi, Iktisadi ve Idari Bilimler Fakultesi, Ekonometri Bolumu, Antalya, Turkiye)

  • Ayça Büyükyılmaz Ercan

    (Akdeniz Universitesi, Iktisadi ve Idari Bilimler Fakultesi, Ekonometri Bolumu, Antalya, Turkiye)

Abstract

Cryptocurrency emerged as an alternative medium of exchange developed after the 2008 global financial crisis to replace the traditional money system. Cryptocurrencies have become increasingly popular because of their fast and secure transactions, elimination of intermediaries, and low cost. However, due to the high risk–return ratio arising from sharp fluctuations in the cryptomoney market, studies have emphasized that the risks of cryptocurrencies should be considered in addition to their returns. This study investigates the effects of positive and negative shocks on the volatility of the rates of return on cryptocurrencies. In this direction, a return series was created by choosing BTC, ETH, XRP, ADA, LTC, BCH, XLM, LINK, TRX, and DOGE cryptocurrencies with high market values. The volatility of these return series was analyzed using symmetric and asymmetric conditional heteroskedasticity models. Although the data set period varies for each cryptocurrency, the largest dataset covers the period from January 1, 2017, to January 16, 2021. The findings show that negative shocks in BTC, ADA, and LINK return series have more effect on volatility than positive shocks. Alternatively, it was concluded that positive shocks have a greater effect on volatility in ETH, XRP, LTC, BCH, XLM, TRX, DOGE return series. Therefore, for the data used in this study, it has been shown that the asymmetric conditional heteroskedasticity models give more meaningful results than the symmetric conditional heteroskedasticity models in modeling the volatility of the return series.

Suggested Citation

  • Fatih Kazova & Ayça Büyükyılmaz Ercan, 2021. "Comparative Analysis of the Volatility Structure of Cryptocurrencies," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(35), pages 33-57, December.
    • Handle: RePEc:ist:ekoist:v:0:y:2021:i:35:p:33-57
    DOI: 10.26650/ekoist.2021.36.984568
    as

    Download full text from publisher

    File URL: https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/01B846E4730048F5816F435C2499B213
    Download Restriction: no
    File URL: https://iupress.istanbul.edu.tr/en/journal/ekoist/article/kripto-para-birimlerinin-volatilite-yapilarinin-karsilastirmali-analizi
    Download Restriction: no
    File URL: https://libkey.io/10.26650/ekoist.2021.36.984568?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. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    3. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    4. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    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. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    2. Bauer, Rob M M J & Nieuwland, Frederick G M C & Verschoor, Willem F C, 1994. "German Stock Market Dynamics," Empirical Economics, Springer, vol. 19(3), pages 397-418.
    3. Estrada, Javier, 1995. "Empirical evidence on the impact of European insider trading regulations," DEE - Working Papers. Business Economics. WB 7068, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    4. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
    5. Mohammad Najand & John Griffith & David C Marlett, 2007. "Do life insurance stocks provide superior returns?," Journal of Asset Management, Palgrave Macmillan, vol. 8(1), pages 52-57, May.
    6. Theodore E. Nijman & Roel Beetsma, 1991. "Empirical Tests of a Simple Pricing Model for Sugar Futures," Annals of Economics and Statistics, GENES, issue 24, pages 121-131.
    7. Li, Qi & Yang, Jian & Hsiao, Cheng & Chang, Young-Jae, 2005. "The relationship between stock returns and volatility in international stock markets," Journal of Empirical Finance, Elsevier, vol. 12(5), pages 650-665, December.
    8. De Santis, Giorgio & imrohoroglu, Selahattin, 1997. "Stock returns and volatility in emerging financial markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 561-579, August.
    9. Pandey, Ajay, 2003. "Modeling and Forecasting Volatility in Indian Capital Markets," IIMA Working Papers WP2003-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    10. Maixé-Altés, J. Carles & Iglesias, Emma M., 2009. "Domestic monetary transfers and the inland bill of exchange markets in Spain (1775-1885)," Journal of International Money and Finance, Elsevier, vol. 28(3), pages 496-521, April.
    11. LINTON, Olivier & PERRON, Benoît, 1999. "The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model," Cahiers de recherche 9911, Universite de Montreal, Departement de sciences economiques.
    12. Verbeek, Marno, 2007. "A Guide to Modern Econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 125-132.
    13. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    14. Jorge Caiado, 2004. "Modelling And Forecasting The Volatility Of The Portuguese Stock Index Psi-20," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 9(1), pages 3-21.
    15. Steeley, James M., 2006. "Volatility transmission between stock and bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(1), pages 71-86, February.
    16. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.
    17. Peter Christoffersen & Redouane Elkamhi & Bruno Feunou & Kris Jacobs, 2010. "Option Valuation with Conditional Heteroskedasticity and Nonnormality," The Review of Financial Studies, Society for Financial Studies, vol. 23(5), pages 2139-2183.
    18. Ventosa-Santaulària, Daniel & Mendoza V., Alfonso, 2005. "Non Linear Moving-Average Conditional Heteroskedasticity," MPRA Paper 58769, University Library of Munich, Germany.
    19. Shields, Kalvinder K, 1997. "Threshold Modelling of Stock Return Volatility on Eastern European Markets," Economic Change and Restructuring, Springer, vol. 30(2-3), pages 107-125.
    20. Madhusudan Karmakar, 2007. "Asymmetric Volatility and Risk-return Relationship in the Indian Stock Market," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 8(1), pages 99-116, January.

    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:ist:ekoist:v:0:y:2021:i:35:p:33-57. 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: Istanbul University Press Operational Team (Ertuğrul YAŞAR) (email available below). General contact details of provider: https://edirc.repec.org/data/ifisttr.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.