SHORT AND LONG RUN EFFECTS OF THE AMERICAN STOCK EXCHANGE ON THE TURKISH STOCK EXCHANGE: THE ARDL BOUNDS TEST APPROACH

Year 2025, Volume: 6 Issue: 1, 1 - 17, 30.04.2025

Taylan Taner Doğan

https://doi.org/10.53280/jer.1640504

Abstract

This study aims to analyze the short and long-run effects of the United States stock market returns and volatility
on the Turkish Stock Exchange. The Dow Jones Industiral (DJI) index is used to represent the American Stock
Exchange and the BIST 30 index is used to represent the Turkish Stock Exchange. The data set includes daily
returns between July 1, 2021 and September 27, 2024. Autoregressive Distributed Lag (ARDL) model and
Generalized Autoregressive Conditional Variance (GARCH) based volatility variables are used for model
estimation. The Bai-Perron test detected four different structural breaks and these breaks are included in the
model. The results show that DJI returns have no effect on BIST 30 in the short run, but indicate a positive and
significant relationship in the long run. On the contrary, DJI volatility has significant and variable / mixed
effects on the Turkish stock market returns in the short run. The findings emphasize the impact of global
financial market integration and volatility on local stock market performance.

Keywords

Stock Market, Time-Series Models, Volatility Forecasting, Stock Market Forecasting

AMERİKAN MENKUL KIYMETLER BORSASININ TÜRKİYE MENKUL KIYMETLER BORSASI ÜZERİNDEKİ KISA VE UZUN DÖNEM ETKİSİ: ARDL SINIR TESTİ YAKLAŞIMI

Abstract

Bu çalışma, Amerikan Menkul Kıymetler Borsası getirileri ve oynaklığının Türkiye Menkul Kıymetler Borsası
üzerindeki kısa ve uzun dönem etkilerini analiz etmeyi amaçlamaktadır. Amerikan Menkul Kıymetler Borsasını
temsilen Dow Jones Industrial (DJI) endeksi ve Türkiye Menkul Kıymetler Borsasını temsilen ise BIST 30
endeksi kullanılmaktadır. Veri seti, 1 Temmuz 2021 ile 27 Eylül 2024 tarihleri arasındaki günlük getirileri
içermektedir. Model tahminleri için Otoregresif Dağıtılmış Gecikme (ARDL) modeli ve Genelleştirilmiş
Otoregresif Koşullu Varyans (GARCH) tabanlı oynaklık değişkenleri kullanılmıştır. Bai-Perron testi, dört
farklı yapısal kırılma tespit etmiş ve bu kırılmalar modele dahil edilmiştir. Sonuçlar, DJI getirilerinin kısa
dönemde BIST 30 üzerinde hiçbir bir etkisinin olmadığını, ancak uzun dönemde pozitif ve anlamlı bir ilişkiye
işaret ettiğini göstermektedir. Buna karşın, DJI oynaklığı Türkiye Borsası getirileri üzerinde kısa dönemde
anlamlı ve değişken / karışık etkiler yaratmaktadır. Bulgular, küresel finansal piyasaların entegrasyonu ve
oynaklık faktörünün yerel borsa performansı üzerindeki etkisini vurgulamaktadır.

Keywords

Menkul Kıymetler Borsası, Zaman Serileri Modelleri, Oynaklık Öngörüsü, Finansal Piyasalar Öngörüsü

References

• Ameziane, A., & Benyacoub, A. (2022). The effect of exchange rate volatility on economic growth in 14 emerging countries: Panel CS-ARDL approach. Journal of Risk and Financial Management, 15(11), 499.
• Arı, I. (2021). Financial time series volatility and macroeconomic variables: A COGARCH-ARDL approach. In A. R. Fomby & A. Tkachenko (Eds.), Econometric Analysis of Financial and Economic Time Series (pp. 213-230).
• Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78.
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Bollerslev, T., Chou, R. Y., & Kroner, K. F. (1992). ARCH modeling in finance: A review of the theory and empirical evidence. Journal of Econometrics, 52(1-2), 5-59.
• Chen, L., & Wang, Y. (2023). The dynamic relationship between stock prices and macroeconomic indicators: Evidence from ARDL and Granger causality tests. Journal of Financial Analysis, 45(2), 210-225.
• Chow, M., McAleer, M., & Sequeira, J. M. (2017). The impact of exchange rate volatility on stock market integration in Southeast Asian markets. Journal of International Financial Markets, Institutions and Money, 50, 46-65.
• Cipollini, F., & Gallo, G. M. (2019). Modelling volatility with GARCH models. In Handbook of Statistics, 41, 99-130.
• Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276.
• Kumeka, T. (2022). Exchange rate shocks and foreign trade performance in ECOWAS countries: Panel ARDL analysis. SSRN Electronic Journal.
• Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159-178.
• Lee, K., Park, J., & Kim, S. (2024). Oil price shocks and sectoral stock returns: An ARDL approach. Energy Economics Review, 36(1), 55-72.
• Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37(17), 1979-1990.
• Ng, S., & Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69(6), 1519-1554.
• Nkoro, E., & Uko, A. K. (2016). Autoregressive Distributed Lag (ARDL) cointegration technique: Application and interpretation. Journal of Statistical and Econometric Methods, 5(4), 63-91.
• Patel, R., & Kumar, M. (2023). BRICS stock markets and macroeconomic factors: A comparative analysis using ARDL models. Emerging Markets Journal, 12(3), 99-117.
• Pesaran, M. H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration analysis. In S. Strom (Ed.), Econometrics and economic theory in the 20th century: The Ragnar Frisch Centennial Symposium (pp. 371-413). Cambridge University Press.
• Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
• Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
• Poon, S.-H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
• Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
• Smith, J., & Taylor, R. (2022). Exchange rate volatility and stock returns: Evidence from developed markets. International Review of Financial Studies, 14(2), 123-140.