IDEAS home Printed from https://ideas.repec.org/a/mth/ber888/v11y2021i1p92-108.html
   My bibliography  Save this article

Time Series Dynamics of Short Term Interest Rates in Turkey

Author

Listed:
  • Emel Siklar
  • Ilyas Siklar

Abstract

Interest rate functions as the cornerstone for the heavy majority of the financial models. The high volatility in interest rates in the financial crisis of 2008/09 and resulting increased uncertainty led many researchers to focus on modeling the dynamics of changes in short term interest rates. This study aims to analyze the volatility of short-term interest rate in Turkey in terms of overnight repo rate and to forecast this rate for the next six months by modelling this volatility. For this purpose, the ARCH family models like ARCH, GARCH and EGARCH were preferred to use since they are the most common methods in the literature. Using the weekly frequency data for the period of January 2002 - January 2021, the model that best describes the stochastic volatility in the data was found to be the GARCH (1.1) model. As a result of the fact that the in-sample estimates were found sufficient, the interest rate estimates for the next 6 months were realized.

Suggested Citation

  • Emel Siklar & Ilyas Siklar, 2021. "Time Series Dynamics of Short Term Interest Rates in Turkey," Business and Economic Research, Macrothink Institute, vol. 11(1), pages 92-108, March.
  • Handle: RePEc:mth:ber888:v:11:y:2021:i:1:p:92-108
    as

    Download full text from publisher

    File URL: http://www.macrothink.org/journal/index.php/ber/article/view/18229/14232
    Download Restriction: no

    File URL: http://www.macrothink.org/journal/index.php/ber/article/view/18229
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fahad Javed Malik & Mohammad Nishat, 2017. "Real interest rate volatility in the Pakistani economy: A regime switching approach," Business Review, School of Economics and Social Sciences, IBA Karachi, vol. 12(2), pages 22-32, July-Dece.
    2. Sudipto Sarkar & Mohamed Ariff, 2002. "The effect of interest rate volatility on treasury yields," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 667-672.
    3. Carl Chiarella & Xue-Zhong He & Christina Sklibosios Nikitopoulos, 2015. "Modelling Interest Rate Dynamics," Dynamic Modeling and Econometrics in Economics and Finance, in: Derivative Security Pricing, edition 127, chapter 0, pages 439-467, Springer.
    4. Carl Chiarella & Xue-Zhong He & Christina Sklibosios Nikitopoulos, 2015. "Derivative Security Pricing," Dynamic Modeling and Econometrics in Economics and Finance, Springer, edition 127, number 978-3-662-45906-5, July-Dece.
    5. Smith, Daniel R, 2002. "Markov-Switching and Stochastic Volatility Diffusion Models of Short-Term Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 183-197, April.
    6. Hideyuki Takamizawa, 2015. "Predicting Interest Rate Volatility Using Information on the Yield Curve," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 347-386, September.
    7. 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.
    8. Joslin, Scott & Konchitchki, Yaniv, 2018. "Interest rate volatility, the yield curve, and the macroeconomy," Journal of Financial Economics, Elsevier, vol. 128(2), pages 344-362.
    9. Brousseau, Vincent & Durré, Alain, 2013. "Interest rate volatility: a consol rate-based measure," Working Paper Series 1505, European Central Bank.
    10. Hou, Ai Jun & Suardi, Sandy, 2011. "Modelling and forecasting short-term interest rate volatility: A semiparametric approach," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 692-710, September.
    11. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
    12. Smile Dube & Yan Zhou, 2013. "South Africa¡¯s Short and Long Term Interest Rates: A Threshold Cointegration Analysis," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 187-211, June.
    13. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
    14. Scott W. Hegerty, 2014. "Interest-rate volatility and volatility transmission in nine Latin American countries," Applied Financial Economics, Taylor & Francis Journals, vol. 24(13), pages 927-937, July.
    15. Sebastian Edwards & Raul Susmel, 2003. "Interest-Rate Volatility in Emerging Markets," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 328-348, May.
    16. Bali, Turan G., 2000. "Testing the Empirical Performance of Stochastic Volatility Models of the Short-Term Interest Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 191-215, June.
    17. Wehnam Peter Dabale & Nelson Jagero, 2013. "Causes of Interest Rate Volatility in Nigeria," International Journal of Financial Economics, Research Academy of Social Sciences, vol. 1(1), pages 42-47.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emel SIKLAR & Ilyas SIKLAR, 2022. "Does Foreign Direct Investment Affect Macroeconomic Dynamics? An S-VAR Approach for Turkey," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 8(3), pages 85-103, 09-2022.

    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. Christiansen, Charlotte, 2008. "Level-ARCH short rate models with regime switching: Bivariate modeling of US and European short rates," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 925-948, December.
    2. Daniel R. Smith & Christophe Parignon, 2004. "Modeling Yield-Factor Volatility," Econometric Society 2004 Australasian Meetings 307, Econometric Society.
    3. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    4. Kanungo, Rama Prasad, 2021. "Uncertainty of M&As under asymmetric estimation," Journal of Business Research, Elsevier, vol. 122(C), pages 774-793.
    5. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    6. Poshakwale, Sunil S. & Mandal, Anandadeep, 2016. "Determinants of asymmetric return comovements of gold and other financial assets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 229-242.
    7. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    8. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    9. Karamé, Frédéric, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Econometrics and Statistics, Elsevier, vol. 8(C), pages 204-230.
    10. Aymen Ben Rejeb, 2013. "Volatility spillovers and contagion: an empirical analysis of structural changes in emerging market volatility," Economics Bulletin, AccessEcon, vol. 33(1), pages 56-71.
    11. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    12. Aymen Ben Rejeb & Adel Boughrara, 2015. "Financial integration in emerging market economies: Effects on volatility transmission and contagion," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 15(3), pages 161-179, September.
    13. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    14. Yanlin Shi, 2023. "Long memory and regime switching in the stochastic volatility modelling," Annals of Operations Research, Springer, vol. 320(2), pages 999-1020, January.
    15. Emenike Kalu O., 2017. "The Interrelationship between Crude Oil Price Volatility and Money Market Rate Volatility in a Developing, Oil-Producing Economy," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 3(1), pages 28-47.
    16. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    17. Turan Bali, 2007. "Modeling the dynamics of interest rate volatility with skewed fat-tailed distributions," Annals of Operations Research, Springer, vol. 151(1), pages 151-178, April.
    18. Andres KUUSK & Tiiu Paas & Karmen Viikmaa, 2011. "Financial contagion of the 2008 crisis: is there any evidence of financial contagion from the US to the Baltic states," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 2, pages 61-76, December.
    19. Asif Mahmood, 2016. "Transmission of Volatility of Money Market Overnight Repo Rate along the Yield Curve in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 12, pages 1-18.
    20. Bali, Turan G. & Mo, Hengyong & Tang, Yi, 2008. "The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 269-282, February.

    More about this item

    Keywords

    Volatility; GARCH; EGARCH; Turkey;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - 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:mth:ber888:v:11:y:2021:i:1:p:92-108. 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: Technical Support Office (email available below). General contact details of provider: http://www.macrothink.org/journal/index.php/ber .

    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.