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Dergiler / Adam Akademi Sosyal Bilimler Dergisi / 2026 / Cilt: 16 Sayı: 1

BIST100 ile ABD Hisse Senedi Piyasaları Arasında Getiri ve Volatilite Yayılımı

Return and Volatility Spillovers between XU100 and US Stock Markets

Ömer Kalav(İstanbul Gedik Üniversitesi İİSBF İşletme Bölümü,)0000-0002-3098-8086
Sayfa
75–92
Yayın Tarihi
2026-05-14
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Elde edilen bulgular, ABD hisse senedi piyasalarından BIST100 endeksine doğru tek yönlü volatilite yayılımı olduğunu göstermektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Finansal piyasaların giderek artan entegrasyonu, bir ülkede meydana gelen ekonomik gelişmelerin diğer ülkelerin finansal piyasalarını etkilemesine yol açmaktadır.
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Temel Bulgular & Veri:Bu çalışma, Türkiye hisse senedi piyasasını temsil eden BIST100 endeksi ile ABD hisse senedi piyasalarını temsil eden NASDAQ ve Dow Jones endeksleri arasındaki getiri ve volatilite yayılım ilişkisini incelemeyi amaçlamaktadır.
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Sonuç & Katkı:Elde edilen bulgular, ABD hisse senedi piyasalarından BIST100 endeksine doğru tek yönlü volatilite yayılımı olduğunu göstermektedir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2015 Verileri
⚙️Değişkenler:XU100 · NASDQ · Dow jones

Özet

Finansal piyasaların giderek artan entegrasyonu, bir ülkede meydana gelen ekonomik gelişmelerin diğer ülkelerin finansal piyasalarını etkilemesine yol açmaktadır. Bu çalışma, Türkiye hisse senedi piyasasını temsil eden BIST100 endeksi ile ABD hisse senedi piyasalarını temsil eden NASDAQ ve Dow Jones endeksleri arasındaki getiri ve volatilite yayılım ilişkisini incelemeyi amaçlamaktadır. Çalışmada 13 Mart 2015 ile 13 Mart 2024 tarihleri arasındaki günlük kapanış verileri kullanılmıştır. Analizde volatilite yayılım etkilerini belirlemek amacıyla BEKK-GARCH modeli, zamanla değişen korelasyon yapısını incelemek için ise DCC-GARCH modeli uygulanmıştır. Ayrıca uzun dönem ilişkilerin varlığı ARDL sınır testi ve Johansen eş bütünleşme testi ile analiz edilmiştir. Elde edilen bulgular, ABD hisse senedi piyasalarından BIST100 endeksine doğru tek yönlü volatilite yayılımı olduğunu göstermektedir. Ayrıca piyasalar arasında genel olarak pozitif yönlü bir getiri ilişkisi tespit edilmiştir. Uzun dönem analiz sonuçları ise fiyat serileri arasında eş bütünleşme bulunmadığını ancak getiri serileri arasında uzun dönemli bir ilişki olduğunu ortaya koymaktadır Anahtar Kelimeler: Volatilite Yayılımı, BIST100, NASDAQ, Dow Jones, DCC-GARCH, BEKK-GARCH JEL Kodu: G15, C58

Abstract

The integration of financial markets means that economic events in one part of the world can have ripple effects globally. A financial crisis in a major economy such as US. economy can lead to reduced investor confidence worldwide, impacting stock markets, currency values, and economic growth in various countries. By using daily closing price, this study aims to examine the time-varying and Spillover effect between the XU100, NASDAQ and Dow Jones indices over the period between 03/13/2015 and 03/13/2024. The results of BEKK-GARCH model show that volatility shocks of returns in US stock market namely NASDAQ and DOW Jones transferred to Turkish stock markets (XU100). Also, there is spillover effect from US stock market to XU100. This effect in one-side. Based on DCC-GARCH results there is generally positive relationship between returns of US stock market and XU100 return. In additional, although there is no any long run relationship between price of two stock market, there is long run relationship between returns of two markets. These results can help investors and market participants understand how risks and returns interact in different markets. It can also provide an important source of information for developing effective portfolio management strategies. Keywords: Volatility Spillover, BIST100, NASDAQ, Dow Jones, DCC-GARCH, BEKK-GARCH JEL Codes: G15, C58

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Bu Makaleye Atıf Yap

Kalav, Ö. (2026). BIST100 ile ABD Hisse Senedi Piyasaları Arasında Getiri ve Volatilite Yayılımı. Adam Akademi Sosyal Bilimler Dergisi, Cilt: 16 Sayı: 1, 75–92. https://doi.org/10.31679/adamakademi.1540706

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Kaynakça (38)

  1. Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance Research Letters, 38, 101604. https://doi.org/10.1016/j.frl.2020.101604
  2. Baele, L. (2005). Volatility Spillover Effects in European Equity Markets. Journal of Financial and Quantitative Analysis, 40(2), 373–401. https://doi.org/10.1017/S0022109000002350
  3. BenSaïda, A., Boubaker, S., & Nguyen, D. K. (2018). The shifting dependence dynamics between the G7 stock markets. Quantitative Finance, 18(5), 801–812. https://doi.org/10.1080/14697688.2017.1419628
  4. Bissoondoyal-Bheenick, E., Brooks, R., Chi, W., & Do, H. X. (2018). Volatility spillover between the US, Chinese and Australian stock markets. Australian Journal of Management, 43(2), 263–285. https://doi.org/10.1177/0312896217717305
  5. Chan, S.-G. (2010, December 1). Volatility spillovers of the major stock markets in ASEAN-5 with the U.S. and Japanese stock markets. https://www.semanticscholar.org/paper/Volatility-spillovers-of-the-major-stock-markets-in-Chan/8574d24ff29426d6308c0bb24855e990ca9ded37
  6. Chevallier, J., Nguyen, D. K., Siverskog, J., & Uddin, G. S. (2018). Market integration and financial linkages among stock markets in Pacific Basin countries. Journal of Empirical Finance, 46, 77–92. https://doi.org/10.1016/j.jempfin.2017.12.006
  7. Chow, H. K. (2017). Volatility Spillovers and Linkages in Asian Stock Markets. Emerging Markets Finance and Trade, 53(12), 2770–2781. https://doi.org/10.1080/1540496X.2017.1314960
  8. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427. https://doi.org/10.2307/2286348
  9. Diebold, F. X., & Yilmaz, K. (2009). Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets. The Economic Journal, 119(534), 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  10. Engle, R. (2002a). Dynamic Conditional Correlation. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487
  11. Engle, R. (2002b). Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics, 20(3), 339–350.
  12. Engle, R. F., & Kroner, K. F. (1995). Multivariate Simultaneous Generalized Arch. Econometric Theory, 11(1), 122–150.
  13. Engle, R., & Sheppard, K. (2001). Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH (NBER Working Paper 8554). National Bureau of Economic Research, Inc. https://econpapers.repec.org/paper/nbrnberwo/8554.htm
  14. Herranz, E. (2017). Unit root tests. WIREs Computational Statistics, 9(3), e1396. https://doi.org/10.1002/wics.1396
  15. Hwang, J.-K. (2023). RETURN AND VOLATILITY SPILLOVER ACROSS STOCK MARKETS OF THE US AND ITS MAJOR TRADING PARTNERS. Journal of International Business and Economics, 23(1), 17–25.
  16. Joshi, P. (2011). Return and Volatility Spillovers Among Asian Stock Markets. Sage Open, 1(1), 2158244011413474. https://doi.org/10.1177/2158244011413474
  17. Kim, D.-H., Lin, S.-C., & Suen, Y.-B. (2010). Dynamic effects of trade openness on financial development. Economic Modelling, 27(1), 254–261. https://doi.org/10.1016/j.econmod.2009.09.005
  18. Kim, J. S., & Ryu, D. (2015). Return and Volatility Spillovers and Cojump Behavior Between the U.S. and Korean Stock Markets. Emerging Markets Finance and Trade, 51(sup1), S3–S17. https://doi.org/10.1080/1540496X.2014.998881
  19. Le, T. N., & Kakinaka, M. (2010). International Transmission of Stock Returns: Mean and Volatility Spillover Effects in Indonesia and Malaysia. Econometrics: Applied Econometrics & Modeling eJournal. https://www.semanticscholar.org/paper/International-Transmission-of-Stock-Returns%3A-Mean-Le- Kakinaka/8041ef6b06d473e6d0b52eb5f3d9cfe4a4d2362e
  20. Li, Y., & Giles, D. E. (2015). Modelling Volatility Spillover Effects Between Developed Stock Markets and Asian Emerging Stock Markets. International Journal of Finance & Economics, 20(2), 155–177. https://doi.org/10.1002/ijfe.1506
  21. Liu, H.-H., & Lin, Y.-C. (2021). Relationships among US S&P500 Stock Index, its Futures and NASDAQ Index Futures with Volatility Spillover and Jump Diffusion: Modeling and Hedging Performance. Bulletin of Applied Economics, 8(1), 121–148.
  22. Liu, Y. A., & Pan, M.-S. (1997). Mean and Volatility Spillover Effects in the U.S. and Pacific–Basin Stock Markets. Multinational Finace Journal, 1(1/1), 47–62.
  23. Majdoub, J., & Mansour, W. (2014). Islamic equity market integration and volatility spillover between emerging and US stock markets. The North American Journal of Economics and Finance, 29, 452–470. https://doi.org/10.1016/j.najef.2014.06.011
  24. Milunovich, G., & Thorp, S. (2006). Valuing volatility spillovers. Global Finance Journal, 17(1), 1–22. https://doi.org/10.1016/j.gfj.2006.06.007
  25. Mohammadi, H., & Tan, Y. (2015). Return and Volatility Spillovers across Equity Markets in Mainland China, Hong Kong and the United States. Econometrics, 3(2), 215–232. https://doi.org/10.3390/econometrics3020215
  26. Mukherjee, K. nath, & Mishra, R. K. (2010). Stock market integration and volatility spillover: India and its major Asian counterparts. Research in International Business and Finance, 24(2), 235–251. https://doi.org/10.1016/j.ribaf.2009.12.004
  27. Mulyadi, M. S., & Anwar, Y. (2012). Return and volatility spillover across USA and Europe (study of American and EU crisis period). African Journal of Business Management, 6(19), 5916–5926. https://doi.org/10.5897/AJBM11.420
  28. Nikmanesh, L., & Mohd Nor, A. H. S. (2019). Causality-in-variance between the stock market and macroeconomic variables in singapore. The Singapore Economic Review, 64(05), 1299–1317. https://doi.org/10.1142/S0217590816500363
  29. Ojaghlou, M. (2024). Co-movements Between Bitcoin and Gold: Multivariate BEKK-GARCH Models. In A. Yelghi, A. Yelghi, M. Apan, & S. Tavangari (Eds.), Computing Intelligence in Capital Market (pp. 37–50). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-57708-6_4
  30. Phillips, P. C. B., & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
  31. Qarni, M. O., & Gulzar, S. (2018). Return and Volatility Spillover across stock markets of China and its Major Trading Partners: Evidence from Shanghai Stock Exchange Crash. Business & Economic Review, 10(3), 1–20. https://doi.org/10.22547/BER/10.3.1
  32. Shen, Y.-Y., Jiang, Z.-Q., Ma, J.-C., Wang, G.-J., & Zhou, W.-X. (2022). Sector connectedness in the Chinese stock markets. Empirical Economics, 62(2), 825–852. https://doi.org/10.1007/s00181-021-02036-0
  33. Sunoto, F., & Dewi, A. S. (2020, April 1). Analisis Spillover Volatilitas Pasar Saham U.S. dan China (Periode 2016-2018). https://www.semanticscholar.org/paper/Analisis-Spillover-Volatilitas-Pasar-Saham-U.S.-dan-Sunoto-Dewi/9e07427f89b172fca72c85dd0a6a8e0d0bea1477
  34. Umer, U. M., Coskun, M., & Kiraci, K. (2018). Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis. Journal of Finance and Economics Research, 3(1), 23–42.
  35. Wolters, J., & Hassler, U. (2006). Unit Root Testing. In O. Hübler & J. Frohn (Eds.), Modern Econometric Analysis: Surveys on Recent Developments (pp. 41–56). Springer. https://doi.org/10.1007/3-540-32693-6_4
  36. Zehri, C. (2021). Stock market comovements: Evidence from the COVID-19 pandemic. Journal of Economic Asymmetries, 24. https://doi.org/10.1016/j.jeca.2021.e00228
  37. Zhang, Y., & Mao, J. (2022). COVID-19′s impact on the spillover effect across the Chinese and U.S. stock markets. Finance Research Letters, 47, 102684. https://doi.org/10.1016/j.frl.2022.102684
  38. Zorgati, I., & Garfatta, R. (2021). Spatial financial contagion during the COVID-19 outbreak: Local correlation approach. Journal of Economic Asymmetries, 24. https://doi.org/10.1016/j.jeca.2021.e00223