IDEAS home Printed from https://ideas.repec.org/a/ist/iujepr/v10y2023i2p435-455.html
   My bibliography  Save this article

Modeling Exchange Rate Volatility in Türkiye: An Empirical Research

Author

Listed:
  • Sinem Kutlu Horvath

    (Istanbul Universitesi, Iktisat Fakultesi, Iktisat Bolumu, Iktisat Teorisi Ana Bilim Dali, Istanbul, Turkiye)

  • Ipek M. Yurttaguler

    (Istanbul Universitesi, Iktisat Fakultesi, Iktisat Bolumu, Iktisat Teorisi Ana Bilim Dali, Istanbul, Turkiye)

Abstract

Exchange rate volatility is a concept that corresponds to the fluctuations around the equilibrium value of the exchange rate and is the main source of exchange rate risk as it adversely affects many variables that can disrupt macroeconomic stability, especially international trade, investments, and capital flows. In this context, empirical estimation and measurement of exchange rate volatility is an issue that needs to be emphasized in terms of its widespread economic effects. The effects of exchange rate volatility on basic macroeconomic variables have created a wide range of research, thus laying the groundwork for a very rich theoretical and empirical literature. This study estimates the volatility in Türkiye using theAutoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) modeling techniques alongside effective exchange rate data for the period of 2003-2022. According to the obtained findings, the study has concluded the GARCH(1,1) model to be the most appropriate model for estimating exchange rate volatility in Türkiye.

Suggested Citation

  • Sinem Kutlu Horvath & Ipek M. Yurttaguler, 2023. "Modeling Exchange Rate Volatility in Türkiye: An Empirical Research," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 10(2), pages 435-455, July.
    • Handle: RePEc:ist:iujepr:v:10:y:2023:i:2:p:435-455
    DOI: 10.26650/JEPR1217028
    as

    Download full text from publisher

    File URL: https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/DDA4BB0515854073B5CEDEEB1607334D
    Download Restriction: no
    File URL: https://iupress.istanbul.edu.tr/en/journal/jepr/article/turkiyede-doviz-kuru-oynakliginin-modellenmesi-ampirik-bir-arastirma
    Download Restriction: no
    File URL: https://libkey.io/10.26650/JEPR1217028?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. Ali Eren ALPER, 2017. "Exchange Rate Volatility and Trade Flows," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 3.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Hooper, Peter & Kohlhagen, Steven W., 1978. "The effect of exchange rate uncertainty on the prices and volume of international trade," Journal of International Economics, Elsevier, vol. 8(4), pages 483-511, November.
    4. 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. Nishimura, Yusaku & Hirayama, Kenjiro, 2013. "Does exchange rate volatility deter Japan-China trade? Evidence from pre- and post-exchange rate reform in China," Japan and the World Economy, Elsevier, vol. 25, pages 90-101.
    2. Alessandra Pasqualina Viola & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto & Wagner Piazza Gaglianone, 2017. "Predicting Exchange Rate Volatility in Brazil: an approach using quantile autoregression," Working Papers Series 466, Central Bank of Brazil, Research Department.
    3. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    4. Yusaku Nishimura & Bianxia Sun, 2018. "China’s Exchange-Rate Regime Reform and Trade Between China and the Eurozone," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(2), pages 450-467, January.
    5. Bajo-Rubio, Oscar & Berke, Burcu & McMillan, David G., 2020. "Exchange rate volatility in the eurozone," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-23.
    6. Rossanto Dwi Handoyo & Agustin Dwi Prihandika Sari & Kabiru Hannafi Ibrahim & Tamat Sarmidi, 2022. "The Volatility of Rupiah Exchange Rate Impact on Main Commodity Exports to the OIC Member States," Economies, MDPI, vol. 10(4), pages 1-18, March.
    7. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    8. Li, Yuming, 1998. "Expected stock returns, risk premiums and volatilities of economic factors1," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 69-97, June.
    9. 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.
    10. repec:wyi:journl:002087 is not listed on IDEAS
    11. Mai, Nhat Chi, 2022. "Tác động của lạm phát đến hoạt động của thị trường chứng khoán ở Việt Nam: Kiểm chứng bằng mô hình GARCH," OSF Preprints azcqd, Center for Open Science.
    12. Daniel L. Thornton, 2007. "The daily and policy-relevant liquidity effects," Working Papers 2007-001, Federal Reserve Bank of St. Louis.
    13. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    14. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    15. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.
    16. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    17. Altaf Muhammad & Zhang Shuguang, 2015. "Impact Of Structural Shifts on Variance Persistence in Asymmetric Garch Models: Evidence From Emerging Asian and European Markets," Romanian Statistical Review, Romanian Statistical Review, vol. 63(1), pages 57-70, March.
    18. P. Kearns & A.R. Pagan, 1993. "Australian Stock Market Volatility: 1875–1987," The Economic Record, The Economic Society of Australia, vol. 69(2), pages 163-178, June.
    19. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    20. Gerard H. Kuper & Daan P. van Soest, 2006. "Does Oil Price Uncertainty Affect Energy Use?," The Energy Journal, , vol. 27(1), pages 55-78, January.
    21. Levent, Korap, 2009. "Enflasyon ve enflasyon belirsizliği ilişkisi için G7 ekonomileri üzerine bir inceleme [An investigation for the inflation and inflation uncertainty relationship upon the G7 economies]," MPRA Paper 19478, University Library of Munich, Germany.

    More about this item

    Keywords

    Effective exchange rate; Volatility; Changing variance; ARCH; GARCH JEL Classification : B22 ; C53 ; F31;
    All these keywords.

    JEL classification:

    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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:ist:iujepr:v:10:y:2023:i:2:p:435-455. 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: Ertugrul YASAR (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.