Borsa İstanbul’un Bölgesel Piyasalar ile Entegrasyonu: Dinamik Koşullu Korelasyonlar ve Yayılım Endeksinden Kanıtlar

Year 2021, Volume: 12 Issue: 3, 941 - 960, 25.09.2021

Gamze Göçmen Yağcılar

Abstract

Çalışmanın amacı, Borsa İstanbul 100 (BİST100) endeksinin bölgesel entegrasyonlarının düzeyini gelişmiş ve gelişen piyasalar çerçevesinde incelemektir. Bu amaçla 09.07.2012-19.02.2021 dönemine ait günlük veri seti kullanılarak MSCI tarafından oluşturulan yedi farklı bölge endeksinin yanı sıra MSCI Dünya ve MSCI Gelişen piyasalar endeksleri ile BİST100 endeksi arasındaki etkileşimler incelenmiştir. Araştırmanın ilk aşamasında iki değişkenli DCC-GARCH yöntemi kullanılarak dinamik koşullu korelasyonlar hesaplanmış ve tüm analizlerde pozitif ve anlamlı katsayılar elde edilmiştir. BİST100 ile ilişkisi en güçlü endeksin Gelişen Avrupa piyasaları, ikinci olarak da Gelişmiş Avrupa piyasaları olduğu bulunmuştur. En zayıf ilişki ise Körfez ülkeleri endeksi ile görülmüştür. Genel olarak Borsa İstanbul’un gelişmekte olan piyasalar ile korelasyonu, gelişmiş piyasalardan daha yüksek çıkmıştır. İkinci aşamada endeksler arasındaki etkileşimin yönünü belirlemek amacıyla Diebold ve Yılmaz (2012) tarafından geliştirilen yayılma endeksi kullanılmıştır. Elde edilen bulgular Borsa İstanbul’un bölgesel endekslerle etkileşiminin zayıf olduğunu ortaya koymaktadır. Bu bulguların gerek finansal entegrasyonun fayda ve maliyetleri noktasında politika yapıcılara gerekse yatırım stratejileri oluşturmaya çalışan portföy yöneticilerine yol göstermesi beklenmektedir.

Keywords

DCC-GARCH, Volatilite Yayılımı, Dinamik Koşullu Korelasyonlar, Finansal Piyasa Entegrasyonu

Integration of Borsa Istanbul with Regional Markets: Evidences from Dynamic Conditional Correlations and Spillover Index

Abstract

The aim of this study is to investigate the integration level of Borsa Istanbul 100 (BİST100) index with regional indexes considering developed and emerging market segments. For this purpose, using a daily data set covering 09.07.2012-19.02.2021 period, interactions between BİST100 index and seven regional indexes constituted by MSCI as well as MSCI World and MSCI Emerging Market indexes are examined. At the first stage of the study, dynamic conditional correlations are estimated by bivariate DCC-GARCH method and positive and significant coefficients are obtained for all index pairs. Highest correlations with BİST100 belong to MSCI emerging Europe and MSCI developed Europe indexes respectively. The weakest correlation of BİST100 is observed with MSCI-GCC index. Conditional correlations of BİST100 and emerging markets are higher than those of BİST100 and developed markets. At the second stage, Diebold and Yilmaz (2012) spillover index is performed in order to determine the direction of interactions. Findings of return and volatility spillovers suggest that the interactions among Borsa İstanbul and regional indexes are weak. Results obtained from the analysis are expected to be useful for both policy makers in the sense of benefits and costs of financial integration and investors in their portfolio decisions.

Keywords

DCC-GARCH, Volatility Spillover, Dynamic Conditional Correlations, Financial Market Integration

References

• Al Nasser, O. & Hajilee, M. (2016). Integrartion of Emerging Stock markets with global stock markets. Research in International Business and Finance, 36, 1-12. http://dx.doi.org/10.1016/j.ribaf.2015.09.025
• Aladesanmi, O., Casalin, F. & Metcalf, H. (2019). Stock Market Integration Between the UK and the US: Evidence over Eigth Decades. Global Finance Journal, 41, 31-43. https://doi.org/10.1016/j.gfj.2018.11.005
• Arouri, M. E. H. & Foulquier, P. (2012). Financial market integration: Theory and empirical results. Economic Modelling, 29, 382-394. https://doi.org/10.1016/j.econmod.2011.11.009
• Aslan, İ. (2019). Bitcoin ve BİST oynaklığın yayılması: Tek ve çok değişkenli GARCH modelleri, Sivas Cumhuriyet Üniversitesi Sosyal Bilimler Enstitüsü Ekonometri Anabilim Dalı, Yayımlanmamış Yüksek Lisans Tezi.
• Bala, D. A. & Takimoto, T. (2017). stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach. Borsa İstanbul Rreview, 17-1, 25-48. http://dx.doi.org/10.1016/j.bir.2017.02.002
• Basher, S. A. & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235-247. http://dx.doi.org/10.1016/j.eneco.2015.11.022
• Baumöhl, E. (2013): Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach. MPRA Paper, No. 43834. Retrieved from https://mpra.ub.uni-muenchen.de/43834/
• Bekaert, G., Harvey, C.R., & Lumsdaine, R.L., 1998. Dating the integration of world equity markets. NBER Working Papers.
• Berine, J., Caporale, G. M., Schulze-Ghattas, M. & Spagnolo, N. (2010). Global and regional spillovers in emerging stock markets: A multivariate GARCH-in-mean analysis. Emerging Markets Review, 11, 250-260. doi:10.1016/j.ememar.2010.05.002
• Bonga-Bonga, L. (2018). Uncovering equity market contagion among BRICS countries: An application of the multivariate GARCH model. The Quarterly Review of Economics and Finance, 67, 36-44. https://doi.org/10.1016/j.qref.2017.04.009
• Can Ergün, Z. ve Karabıyık, C. (2020). Türkiye ve Dünya hisse senedi piyasaları arasındaki getiri ve oynaklık yayılımlarının ölçülmesi: Yayılma endeksi yaklaşımı. Yönetim ve Ekonomi, 27(3), 741-758. Doi: 10.18657/yonveek.686545
• 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
• Chittedi, K. R. (2015). Financial crisis and contagion effects to ındian stock market: ‘DCC-GARCH’ analysis. Global Business Review, 16(1), 50-60. DOI: 10.1177/0972150914553507
• Çelik, İ., Özdemir, A. ve Demir Gülbahar, S. (2018a). Gelişmekte olan ülkelerde getiri ve volatilite yayılımı: NIMPT ülkelerinde VAR-EGARCH uygulaması. Finans, Politik ve Ekonomik Yorumlar Dergisi, 55(636), 9-24.
• Çelik, İ., Özdemir, A. ve Demir Gülbahar, S. (2018b). İslami hisse senedi endeksleri arasında getiri ve volatilite yayılımı: Gelişmiş ve gelişmekte olan piyasalarda çok değişkenli VAR-EGARCH uygulaması. Muhasebe ve Finans İncelemeleri Dergisi, 1 (2), 89-100.
• Damianov, D. S. & Elsayed, A. H. (2020). Does Bitcoin add value to global ındustry protfolios? Economic Letters, 191, 108935. https://doi.org/10.1016/j.econlet.2019.108935
• Daugherty, M. S. & Jithendranathan, T. (2015). A study of linkages between frontier markets and the U.S. equity markets using multivariate GARCH and transfer entropy. Journal of Multinational Financial Management, 32-33, 95-115. http://dx.doi.org/10.1016/j.mulfin.2015.10.003
• Demirgil, H. ve Gök, İ. Y. (2014). Türkiye ve başlıca AB pay piyasaları arasında asimetrik volatilite yayılımı. Yönetim ve Ekonomi Araştırmaları Dergisi, 23, 315-340. Doi: http://dx.doi.org/10.11611/JMER244
• Diebold, F. X. & Yılmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119, 158-171. Retrieved from https://www.sas.upenn.edu/
• Diebold, F. X. & Yılmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28, 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006
• Dimitriou, D., Kenourgios, D. & Simos, T. (2013). Global financial crisis and emerging stock market contagion: A multivarate FIAPARCH-DCC approach. International Review of Financial Analysis, 30, 46-56. http://dx.doi.org/10.1016/j.irfa.2013.05.008
• Do, A., Powell, R., Yong, J. & Singh, A. (2020). Time-varying asymmetric volatility spillover between global markets and China’s A, B and H-shares using EGARCH-and DCC-EGARCH models. North American Journal of Economics and Finance, 54, 101096. https://doi.org/10.1016/j.najef.2019.101096
• Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20.3: 339-350.
• Friedman, T. L. (2005). The World is Flat: A brief history of the twenty-first century. New York: Farrar, Straus and Giroux.
• Gemici, E. (2020). Gelişmekte olan piyasalarda finansal bağlantılılık. OPUS Uluslararası Toplum Araştırmaları Dergisi, 16(30). DOI: 10.26466/opus. 778653
• Gilenko, E. & Fedorova, E. (2014). Internal and external spillover effects for the BRIC countries: Multivariate GARCH-in-mean approach. Research in International Business and Finance, 31, 32-45. http://dx.doi.org/10.1016/j.ribaf.2013.11.002
• Gjika, D. & Horvath, R. (2013). Stock market comovements in Central Europe: Evidence from the asymmetric DCC model. Economic Modelling, 33, 55-64. http://dx.doi.org/10.1016/j.econmod.2013.03.015
• Guesmi, K., Nguyen, D. K. & Teulon, F. (2013). Further evidence on the determinants of regional stock market ıntegration in Latin America. The European Journal of Comparative Economics, 10(3), 397-413. Retrieved from https://ideas.repec.org/
• Güloğlu, B., Kaya, P. & Aydemir, R. (2016). Volatility transmission among Latin American stock markets under structural breaks. Physica A, 462, 330-340. http://dx.doi.org/10.1016/j.physa.2016.06.093
• Hatipoğlu, M. ve Sekmen, T. (2016). Borsa İstanbul ve gelişmiş ülke borsalarının ortak hareketi üzerine bir çalışma. Research Journal of Politics, Economics and Management, 4(3), 24-35.
• Huwart, Jean-Yves & Loïc Verdier (2013). Chapter 4: A global or semi-global village? (1990s to today), in Economic Globalisation: Origins and consequences. OECD Publishing, Paris.
• Inaba, K.-I. (2020). A global look into stock market comovements. Review of World Economics, 156, 517-555. https://doi.org/10.1007/s10290-019-00370-1.
• Joyo, A. S. & Lefen, L. (2019). Stock market ıntegration of Pakistan with ıts trading partners: a multivariate DCC-GARCH model approach. MPDI, Sustainability, 11(2), 1-23. https://doi.org/10.3390/su11020303
• Kang, S. H., Uddin, G. S., Torster, V. & Yoon, S.-M. (2019). Directional spillover effects between ASEAN and world stock markets. Journal of Multinational Financial Management, 52-53, 100592. https://doi.org/10.1016/j.mulfin.2019.100592
• Kenourgios, D. & Samitas, A. (2011). Equity market ıntegration in emerging Balkan markets. Research in International Business and Finance, 25, 296-307. doi:10.1016/j.ribaf.2011.02.004
• Khalifa, A. A. A., Hammoudeh, S. & Otranto, E. (2014). Patterns of volatility transmission within regime switching across GCC and global markets. International Review of Economics and Finance, 29, 512-524. http://dx.doi.org/10.1016/j.iref.2013.08.002
• Kılıç, Y. ve Buğan, M. F. (2019). Finansal piyasaların entegrasyonu: ABD, AB, Asya piyasaları ve Borsa İstanbul örneği. Sosyal Bilimler Metinleri, 2019(1), 49-61. Retrieved from https://dergipark.org.tr/
• Kırkulak Uludağ, B. & Ezzat, H. (2017). Volatility spillover effect in MENA stock markets: Evidence from Pre- and post-Egiptian revolution. Journal of Yaşar University, 12(45), 32-47. Retrieved from https://dergipark.org.tr/
• Lean, H. H. & Teng, K. T. (2013). Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach. Economic Modelling, 32, 333-342.
• Lee, H. & Kim, H. (2020). Time varying integration of European stock markets and monetary drivers. Journal of Empirical Finance, 58, 369-385. https://doi.org/10.1016/j.jempfin.2020.07.004
• Lou, J. & Wang, S. (2019). The asymmetric high-frequency volatility transmission across international stock markets. Finance Research Letters, 31, 104-109. https://doi.org/10.1016/j.frl.2019.04.025
• Mahbubani, K. (2012, September). The Global village has arrived. Finance and Development, 49(3). Retrieved from www.imf.org, 23.04.2021
• Majdoub, J. & Mansour, W. (2014). Islamic equity market ıntegration and volatility spillover between emerging and US stock markets. North American Journal of Economics and Finance, 29, 452-470.
• McLuhan, M. (1962). The Gutenberg galaxy: the making of typographic man. Canada: University of Toronto Press.
• Narayan, S., Sriananthakumar, S. & Islam, S. Z. (2014). Stock market integration of emerging Asian economies: patterns and causes. Economic Modelling, 39, 19-31. http://dx.doi.org/10.1016/j.econmod.2014.02.012
• Özşahin, Ş. (2017). Yükselen piyasa ekonomilerinde menkul kıymetler borsalarının entegrasyonu: Türkiye ve BRICS ülkeleri üzerine çoklu yapısal kırılmalı eş-bütünleşme analizi. Yönetim ve Ekonomi, 24(2), 601-619.
• Polat, O. (2018). Hisse senedi piyasalarında finansal bağlantılılık analizi. Politik Ekonomik Kuram, 2(1), 73-86.
• Primorac, M. (2012, August 30). IMF Survey: The Global village: connected World drives economic shift. IMF News, World Economy. Retrieved from IMF, 23.04.2021. https://www.imf.org/en/News/Articles/2015/09/28/04/53/sonew083012a
• Robiyanto, R. (2018). Indonesian stock market’s dynamic ıntegration with Asian stock markets and world stock markets. Jurnal Pengurusan, 52, 181-192. https://doi.org/10.17576/pengurusan-2018-52-15
• Sarısoy Guerin, S. (2006). The role of georgraphy in financial and economic integrayion: a comparative analyisis of foreign direct investment, trade and portfolio investment flows. The World Economy, 29(2), 189-209. https://doi.org/10.1111/j.1467-9701.2006.00777.x
• Song, Y., Huang, R., Paramati, S. R. & Zakari, A. (2021). Does economic integration lead financial market integration in the Asian region? Economic Analysis and Policy, 69, 366-377. https://doi.org/10.1016/j.eap.2020.12.003
• Su,X. (2020). Dynamic behaviors and contributing factors of volatility spilloversacross G7 stock markets. North American Journal of Economics and Finance, 53, 101218. https://doi.org/10.1016/j.najef.2020.101218
• Şenol, Z. ve Türkay, H. (2020). Gelişmiş ve gelişmekte olan borsalar arasındaki oynaklık yayılımı. Marmara Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 42(2), 361-385. DOI: 10.14780.muiibd.854527
• Taşdemir, M. & Yalama, A. (2014). Volatility spillover effects in ınterregional equity markets: empirical evidence from Brazil and Turkey. Emerging Markets Finance and Trade, 50:2, 190-202, DOI: 10.2753/REE1540-496X500211
• Wang, P. & Moore, T. (2008). Stock market ıntegration for the transition economies: Time-varying conditional correlation approach. The Manchester School Supplement, 76(s1), 116-133. https://doi.org/10.1111/j.1467-9957.2008.01083.x
• World Inc. (2021). Recommended Reading: The World is Flat, by Thomas L. Friedman. http://www.worldincbook.com/res_book_friedman.html, erişim 23.04.2021.
• Yao, S., He, H., Chen, S. & Ou, j. (2018). Financial liberalization and cross-border market integration: Evidence from China’s stock market. International Review of Economics and Finance, 58, 220-245. http://dx.doi.org/10.1016/j.iref.2018.03.023
• Ziadat, S. A., Herbst, P. & McMillan, D. G. (2020). Inter- and Intra-regional stock market relations for the GCC bloc. Research in International Business and Finance, 54, 101292. https://doi.org/10.1016/j.ribaf.2020.101292