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ABD Finansal Piyasalarındaki Gelişmelerin ve Belirsizliklerin Borsa İstanbul Üzerindeki Asimetrik Etkileri

Year 2020, Volume: 8 Issue: İktisadi ve İdari Bilimler, 33 - 42, 18.12.2020
https://doi.org/10.18506/anemon.617638

Abstract

Bu çalışmada, ABD hisse senedi piyasası ve bu piyasadaki belirsizliklerin yanında ABD Merkez Bankası (FED) para politikalarındaki belirsizliğin Borsa İstanbul (BIST) üzerindeki etkileri incelenmiştir. Bu incelemede, doğrusal olmayan otoregresif gecikmesi dağıtılmış (NARDL) ve doğrusal otoregresif gecikmesi dağıtılmış (ARDL) modellerinden faydalanılmıştır. Elde edilen sonuçlara göre, ABD hisse senedi piyasasındaki değişimlerin BIST üzerinde kısa dönemde pozitif ve uzun dönemde negatif etkilerinin olduğu ve bu etkilerin kısa dönemde asimetrik olduğu gözlemlenmiştir. Buna ek olarak, hem ABD hisse senedi piyasasındaki belirsizliğin hem de FED politikalarındaki belirsizliğin BIST üzerinde asimetrik etkilere sahip olduğu ve bu etkilerin kısa ve uzun dönemde önemli derecede farklı olduğu bulgusuna ulaşılmıştır. Bulgularımız etkin yatırım stratejileri uygulamak ve küresel risklere karşı uygun ekonomi politikalarının belirlenmesi açısından önemli çıkarımlar içermektedir.

References

  • Acemoglu, D., & Scott, A. (1997). Asymmetric business cycles: Theory and time-series evidence. Journal of Monetary Economics, 40(3), 501-533.
  • Aloui, R., Aïssa, M. S. B., & Nguyen, D. K. (2011). Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?. Journal of Banking & Finance, 35(1), 130-141.
  • Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross‐section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.
  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
  • Başarır, Ç. (2018). Korku Endeksi (VIX) ile BIST 100 Arasındaki İlişki: Frekans Alanı Nedensellik Analizi. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 19(2), 177-191.
  • Becker, R., Clements, A. E., & McClelland, A. (2009). The jump component of S&P 500 volatility and the VIX index. Journal of Banking & Finance, 33(6), 1033-1038.
  • Bekaert, G., & Harvey, C. R. (1995). Time‐varying world market integration. The Journal of Finance, 50(2), 403-444.
  • Bessler, D. A., & Yang, J. (2003). The structure of interdependence in international stock markets. Journal of International Money and Finance, 22(2), 261-287.
  • Blair, B. J., Poon, S. H., & Taylor, S. J. (2001). Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns. Journal of Econometrics, 105(1), 5-26.
  • Bloom, N. (2014). Fluctuations in uncertainty. Journal of Economic Perspectives, 28(2), 153-76.
  • Carrieri, F., Errunza, V., & Hogan, K. (2007). Characterizing world market integration through time. Journal of Financial and Quantitative Analysis, 42(4), 915-940.
  • Chicago Board Options Exchange (2015). Guide to the CBOE / CBOT 10 Year Treasury Note Volatility Index (TYVIXSM Index). (Erişim: 03/03/2019), http://www.cboe.com/micro/volatility/tyvix/pdf/tyvixguidepart1.pdf
  • Cho, D. C., Eun, C. S., & Senbet, L. W. (1986). International arbitrage pricing theory: An empirical investigation. The Journal of Finance, 41(2), 313-329.
  • Chowdhury, A. R. (1994). Stock market interdependencies: evidence from the Asian NIEs. Journal of Macroeconomics, 16(4), 629-651.
  • 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(366a), 427-431.
  • Granger, C. W., & Yoon, G. (2002). Hidden cointegration. U of California, Economics Working Paper, (2002-02).
  • Hatipoğlu, M., & Tekin, B. (2017). The Effects of VIX Index, Exchange Rate & Oil Prices on the BIST 100 Index: A Quantile Regression Approach. Ordu Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 7(3), 627-634.
  • Hoffmann, A. O., Post, T., & Pennings, J. M. (2013). Individual investor perceptions and behavior during the financial crisis. Journal of Banking & Finance, 37(1), 60-74.
  • Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-292.
  • Karğın, S., Kayalıdere, K., Güleç, T. C., & Erer, D. (2018). Spillovers Of Stock Return Volatility To Turkish Equity Markets From Germany, France, And America. Dokuz Eylul University Journal of Graduate School of Social Sciences, 20(2), 171-187
  • Kaya, E. (2015). Borsa İstanbul (BIST) 100 endeksi ile Zımni Volatilite (VIX) endeksi arasındaki eş-bütünleşme ve Granger nedensellik. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, 2015(1), 1-6.
  • Kocaarslan, B., Sari, R., & Soytas, U. (2017). Are there any diversification benefits among global finance center candidates in Eurasia?. Emerging Markets Finance and Trade, 53(2), 357-374.
  • Korkmaz, T., & Çevik, E. İ. (2009). Zımni Volatilite Endeksinden Gelişmekte Olan Piyasalara Yönelik Volatilite Yayılma Etkisi. BDDK Bankacilik ve Finansal Piyasalar, 3(2), 87-105.
  • Kumar, M. S., & Persaud, A. (2002). Pure contagion and investors’ shifting risk appetite: analytical issues and empirical evidence. International Finance, 5(3), 401-436.
  • Küçükkaya, E. (2009). Diversification benefits of including Turkish and US stocks in a portfolio. The International Journal of Economic and Social Research,. 5(2), 1-11.
  • Maki, D. (2012). Tests for cointegration allowing for an unknown number of breaks. Economic Modelling, 29(5), 2011-2015.
  • Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55 (3), 703–708.
  • Olgun, H., & Ozdemir, Z. A. (2008). Linkages between the center and periphery stock prices: Evidence from the vector ARFIMA model. Economic Modelling, 25(3), 512-519.
  • Öner, H., İçellioğlu, C. Ş., & Öner, S. (2018). Volatilite Endeksi (VIX) ile Gelişmekte Olan Ülke Hisse Senedi Piyasası Endeksleri Arasındaki Engel-Granger Eş-Bütünleşme ve Granger Nedensellik Analizi. Finansal Araştırmalar ve Çalışmalar Dergisi, 10(18), 110-124.
  • Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371-413.
  • 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 regressions. Biometrica 75 (2), 335–346.
  • Sadeghzadeh, K., & Elmas, B. (2018). Makroekonomik Faktörlerin Hisse Senedi Getirilerine Etkilerinin BIST’de Araştırılması. Muhasebe ve Finansman Dergisi, (80), 207-232.
  • Schorderet, Y., (2003). Asymmetric Cointegration. University of Geneva, Mimeo.
  • Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of Peter Schmidt (pp. 281-314). Springer, New York, NY.
  • Solnik, B. H. (1974). Why Not Diversify Internationally Rather Than Domestically?. Financial Analysts Journal, 30(4), 48-54.
  • Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.
  • Zeren, F., & Koç, M. (2013). Analyzing Integration between Stock Market of Turkey and G8 Nations with Maki Cointegration Test. Journal of Applied Finance and Banking, 3(6), 135.

The Asymmetric Effects of Developments and Uncertainties in US Financial Markets on Borsa Istanbul

Year 2020, Volume: 8 Issue: İktisadi ve İdari Bilimler, 33 - 42, 18.12.2020
https://doi.org/10.18506/anemon.617638

Abstract

In this study, the effects of US stock market, US stock market uncertainty and the Federal Reserve’s (FED) monetary policy uncertainty on Borsa Istanbul (BIST) are investigated. In this investigation, nonlinear and linear autoregressive distributed lag (NARDL and ARDL) models are used. It is observed that changes in US stock market have positive and negative impacts on the BIST in the short- and long-term, respectively, and these effects are asymmetric in the short-term. Furthermore, it is found that the uncertainties in the US stock market and the FED policies have different and asymmetric effects on the BIST in the short- and long-term. Our findings have important implications for implementing effective investment strategies and determining appropriate economic policies against global risks.

References

  • Acemoglu, D., & Scott, A. (1997). Asymmetric business cycles: Theory and time-series evidence. Journal of Monetary Economics, 40(3), 501-533.
  • Aloui, R., Aïssa, M. S. B., & Nguyen, D. K. (2011). Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?. Journal of Banking & Finance, 35(1), 130-141.
  • Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross‐section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.
  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
  • Başarır, Ç. (2018). Korku Endeksi (VIX) ile BIST 100 Arasındaki İlişki: Frekans Alanı Nedensellik Analizi. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 19(2), 177-191.
  • Becker, R., Clements, A. E., & McClelland, A. (2009). The jump component of S&P 500 volatility and the VIX index. Journal of Banking & Finance, 33(6), 1033-1038.
  • Bekaert, G., & Harvey, C. R. (1995). Time‐varying world market integration. The Journal of Finance, 50(2), 403-444.
  • Bessler, D. A., & Yang, J. (2003). The structure of interdependence in international stock markets. Journal of International Money and Finance, 22(2), 261-287.
  • Blair, B. J., Poon, S. H., & Taylor, S. J. (2001). Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns. Journal of Econometrics, 105(1), 5-26.
  • Bloom, N. (2014). Fluctuations in uncertainty. Journal of Economic Perspectives, 28(2), 153-76.
  • Carrieri, F., Errunza, V., & Hogan, K. (2007). Characterizing world market integration through time. Journal of Financial and Quantitative Analysis, 42(4), 915-940.
  • Chicago Board Options Exchange (2015). Guide to the CBOE / CBOT 10 Year Treasury Note Volatility Index (TYVIXSM Index). (Erişim: 03/03/2019), http://www.cboe.com/micro/volatility/tyvix/pdf/tyvixguidepart1.pdf
  • Cho, D. C., Eun, C. S., & Senbet, L. W. (1986). International arbitrage pricing theory: An empirical investigation. The Journal of Finance, 41(2), 313-329.
  • Chowdhury, A. R. (1994). Stock market interdependencies: evidence from the Asian NIEs. Journal of Macroeconomics, 16(4), 629-651.
  • 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(366a), 427-431.
  • Granger, C. W., & Yoon, G. (2002). Hidden cointegration. U of California, Economics Working Paper, (2002-02).
  • Hatipoğlu, M., & Tekin, B. (2017). The Effects of VIX Index, Exchange Rate & Oil Prices on the BIST 100 Index: A Quantile Regression Approach. Ordu Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 7(3), 627-634.
  • Hoffmann, A. O., Post, T., & Pennings, J. M. (2013). Individual investor perceptions and behavior during the financial crisis. Journal of Banking & Finance, 37(1), 60-74.
  • Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-292.
  • Karğın, S., Kayalıdere, K., Güleç, T. C., & Erer, D. (2018). Spillovers Of Stock Return Volatility To Turkish Equity Markets From Germany, France, And America. Dokuz Eylul University Journal of Graduate School of Social Sciences, 20(2), 171-187
  • Kaya, E. (2015). Borsa İstanbul (BIST) 100 endeksi ile Zımni Volatilite (VIX) endeksi arasındaki eş-bütünleşme ve Granger nedensellik. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, 2015(1), 1-6.
  • Kocaarslan, B., Sari, R., & Soytas, U. (2017). Are there any diversification benefits among global finance center candidates in Eurasia?. Emerging Markets Finance and Trade, 53(2), 357-374.
  • Korkmaz, T., & Çevik, E. İ. (2009). Zımni Volatilite Endeksinden Gelişmekte Olan Piyasalara Yönelik Volatilite Yayılma Etkisi. BDDK Bankacilik ve Finansal Piyasalar, 3(2), 87-105.
  • Kumar, M. S., & Persaud, A. (2002). Pure contagion and investors’ shifting risk appetite: analytical issues and empirical evidence. International Finance, 5(3), 401-436.
  • Küçükkaya, E. (2009). Diversification benefits of including Turkish and US stocks in a portfolio. The International Journal of Economic and Social Research,. 5(2), 1-11.
  • Maki, D. (2012). Tests for cointegration allowing for an unknown number of breaks. Economic Modelling, 29(5), 2011-2015.
  • Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55 (3), 703–708.
  • Olgun, H., & Ozdemir, Z. A. (2008). Linkages between the center and periphery stock prices: Evidence from the vector ARFIMA model. Economic Modelling, 25(3), 512-519.
  • Öner, H., İçellioğlu, C. Ş., & Öner, S. (2018). Volatilite Endeksi (VIX) ile Gelişmekte Olan Ülke Hisse Senedi Piyasası Endeksleri Arasındaki Engel-Granger Eş-Bütünleşme ve Granger Nedensellik Analizi. Finansal Araştırmalar ve Çalışmalar Dergisi, 10(18), 110-124.
  • Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371-413.
  • 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 regressions. Biometrica 75 (2), 335–346.
  • Sadeghzadeh, K., & Elmas, B. (2018). Makroekonomik Faktörlerin Hisse Senedi Getirilerine Etkilerinin BIST’de Araştırılması. Muhasebe ve Finansman Dergisi, (80), 207-232.
  • Schorderet, Y., (2003). Asymmetric Cointegration. University of Geneva, Mimeo.
  • Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of Peter Schmidt (pp. 281-314). Springer, New York, NY.
  • Solnik, B. H. (1974). Why Not Diversify Internationally Rather Than Domestically?. Financial Analysts Journal, 30(4), 48-54.
  • Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.
  • Zeren, F., & Koç, M. (2013). Analyzing Integration between Stock Market of Turkey and G8 Nations with Maki Cointegration Test. Journal of Applied Finance and Banking, 3(6), 135.
There are 38 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Barış Kocaarslan 0000-0003-4492-980X

Publication Date December 18, 2020
Acceptance Date June 10, 2020
Published in Issue Year 2020 Volume: 8 Issue: İktisadi ve İdari Bilimler

Cite

APA Kocaarslan, B. (2020). ABD Finansal Piyasalarındaki Gelişmelerin ve Belirsizliklerin Borsa İstanbul Üzerindeki Asimetrik Etkileri. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(İktisadi ve İdari Bilimler), 33-42. https://doi.org/10.18506/anemon.617638

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