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Fractional Cointegration Analysis Of Stock Market And Exchange Rates: The Case Of Turkey

Author

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  • ERER, Deniz

    (Ege Üniversitesi Sosyal Bilimler Enstitüsü, İktisat Anabilim Dalı)

  • ERER, Elif

    (Ege Üniversitesi Sosyal Bilimler Enstitüsü, İktisat Anabilim Dalı)

  • GÜLEÇ, Tuna Can

    (Celal Bayar Üniversitesi, SBE, Muhasebe ve Finans Anabilim Dalı)

Abstract

Abstract The fluctuations and responses between the exchange rate and the stock market has been a topic of interest for both policy makers and market participants for a long time. The aim of the study is to examine so-called relationship using fractional cointegration analysis. For this purpose, we utilized from Borsa İstanbul and daily exchange rates USD/TRY and EUR/TRY for period 2002:01–2015:04 to determine this relationship. Fractional cointegration analysis indicates presence of an equilibrium in the long term in series and fractional integrated errors show persistent characteristics which indicate long memory. Therefore instead of using classical cointegration we have decided using Geweke and Porter-Hudak fractional cointegration for more accurate results. Results indicate that there is a significant positive cointegration between exchange rates and stock prices in Turkish market Borsa İstanbul. This study contributes to literature by analyzing the phenomenon under long memory conditions in Borsa Istanbul.

Suggested Citation

  • ERER, Deniz & ERER, Elif & GÜLEÇ, Tuna Can, 2016. "Fractional Cointegration Analysis Of Stock Market And Exchange Rates: The Case Of Turkey," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 20(3), pages 80-94.
  • Handle: RePEc:vls:finstu:v:20:y:2016:i:3:p:80-94
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    References listed on IDEAS

    as
    1. Claude Diebolt & Vivien Guiraud, 2005. "A Note On Long Memory Time Series," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(6), pages 827-836, December.
    2. P. S. Sephton, 2002. "Fractional cointegration: Monte Carlo estimates of critical values, with an application," Applied Financial Economics, Taylor & Francis Journals, vol. 12(5), pages 331-335.
    3. Ingolf Dittmann, 2004. "Error Correction Models for Fractionally Cointegrated Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 27-32, January.
    4. Dornbusch, Rudiger & Fischer, Stanley, 1980. "Exchange Rates and the Current Account," American Economic Review, American Economic Association, vol. 70(5), pages 960-971, December.
    5. Solnik, Bruno, 1987. " Using Financial Prices to Test Exchange Rate Models: A Note," Journal of Finance, American Finance Association, vol. 42(1), pages 141-149, March.
    6. Erman Erbaykal & H. Aydin Okuyan, 2007. "The Relationship Between Stock Prices and Exchange Rates: An Empirical Study on Emerging Markets," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 1(1), pages 77-90.
    7. Nieh, Chien-Chung & Lee, Cheng-Few, 2001. "Dynamic relationship between stock prices and exchange rates for G-7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(4), pages 477-490.
    8. Alok Kumar Mishra, 2004. "Stock Market and Foreign Exchange Market in India: Are they Related?," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 5(2), pages 209-232, September.
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    More about this item

    Keywords

    Financial Markets; Fractional Integration; Fractional Cointegration;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • A1 - General Economics and Teaching - - General Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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