IDEAS home Printed from https://ideas.repec.org/a/prg/jnlaop/v2016y2016i2id525p3-17.html
   My bibliography  Save this article

Some stylised facts about the exchange rate behaviour of Central European currencies

Author

Listed:
  • Jan Vejmělek

Abstract

The paper investigates developments of exchange rate time series of Central European currencies and tries to find evidence of some stylised facts. Statistical methods and an econometric approach to the univariate time series modelling of high-frequency data, i.e., daily, are used. The main conclusions are as follows: (1) All the CE nominal exchange time series are not stationary: nevertheless, stationarity of all the return time series was confirmed. (2) Volatility clustering was proven and the GARCH modelling approach was successfully applied, including asymmetric modelling of volatility. (3) The more flexible an exchange rate regime is, the more volatile the respective currency. This is true for both nominal and real exchange rates. While nominal volatility is lower than real volatility in a system of fixed or less flexible exchange rates, the opposite is true for flexible systems: exchange rate volatility is higher in nominal terms than in real terms.

Suggested Citation

  • Jan Vejmělek, 2016. "Some stylised facts about the exchange rate behaviour of Central European currencies," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2016(2), pages 3-17.
    • Handle: RePEc:prg:jnlaop:v:2016:y:2016:i:2:id:525:p:3-17
    DOI: 10.18267/j.aop.525
    as

    Download full text from publisher

    File URL: http://aop.vse.cz/doi/10.18267/j.aop.525.html
    Download Restriction: free of charge
    File URL: http://aop.vse.cz/doi/10.18267/j.aop.525.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.aop.525?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. Kocenda, Evzen & Valachy, Juraj, 2006. "Exchange rate volatility and regime change: A Visegrad comparison," Journal of Comparative Economics, Elsevier, vol. 34(4), pages 727-753, December.
    2. Fidrmuc, Jarko & Horváth, Roman, 2008. "Volatility of exchange rates in selected new EU members: Evidence from daily data," Economic Systems, Elsevier, vol. 32(1), pages 103-118, March.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Lothian, James R., 1998. "Some new stylized facts of floating exchange rates," Journal of International Money and Finance, Elsevier, vol. 17(1), pages 29-39, February.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Ngo Thai Hung, 2021. "Volatility Behaviour of the Foreign Exchange Rate and Transmission Among Central and Eastern European Countries: Evidence from the EGARCH Model," Global Business Review, International Management Institute, vol. 22(1), pages 36-56, February.
    2. Bogdan Andrei DUMITRESCU & Silvia Maria ROȘCA, 2015. "The exchange rate volatility in the Central and Eastern European Countries," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(603), S), pages 189-198, Summer.
    3. Rachna Mahalwala, 2022. "Analysing exchange rate volatility in India using GARCH family models," SN Business & Economics, Springer, vol. 2(9), pages 1-16, September.
    4. David Büttner & Bernd Hayo & Matthias Neuenkirch, 2012. "The impact of foreign macroeconomic news on financial markets in the Czech Republic, Hungary, and Poland," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 39(1), pages 19-44, February.
    5. Michael Frömmel, 2010. "Volatility Regimes in Central and Eastern European Countries’ Exchange Rates," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(1), pages 2-21, February.
    6. Walther, Thomas & Klein, Tony & Thu, Hien Pham & Piontek, Krzysztof, 2017. "True or spurious long memory in European non-EMU currencies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 217-230.
    7. Daniel Stavarek, 2011. "European exchange rates volatility and its asymmetrical components during the financial crisis," MENDELU Working Papers in Business and Economics 2011-17, Mendel University in Brno, Faculty of Business and Economics.
    8. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    9. Giannellis, Nikolaos & Papadopoulos, Athanasios P., 2011. "What causes exchange rate volatility? Evidence from selected EMU members and candidates for EMU membership countries," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 39-61, February.
    10. repec:agr:journl:v:2(602):y:2015:i:2(602):p:189-198 is not listed on IDEAS
    11. Afees A. Salisu & Ismail O. Fasanya, 2012. "Comparative Performance of Volatility Models for Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 2(3), pages 167-183.
    12. Liang, Yousha & Shi, Kang & Wang, Lisheng & Xu, Juanyi, 2019. "Fluctuation and reform: A tale of two RMB markets," China Economic Review, Elsevier, vol. 53(C), pages 30-52.
    13. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    14. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    15. Tomanova, Lucie, 2013. "Exchange Rate Volatility and the Foreign Trade in CEEC," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 267, Ekonomik Yaklasim Association.
    16. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    17. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    18. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    19. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    20. 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.
    21. Chang, Chia-Lin & Hsu, Hui-Kuang, 2013. "Modelling Volatility Size Effects for Firm Performance: The Impact of Chinese Tourists to Taiwan," MPRA Paper 45691, University Library of Munich, Germany.

    More about this item

    Keywords

    exchange rate; volatility; time series analysis; GARCH models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

    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:prg:jnlaop:v:2016:y:2016:i:2:id:525:p:3-17. 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.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.