Borsa Istanbul Sectoral Connectedness Analysis

Yıl 2024, Cilt: 31 Sayı: 1, 61 - 74, 26.03.2024

Erhan Uluceviz

https://doi.org/10.18657/yonveek.1284521

Öz

This study examines the volatility connectedness among banks, industrials, and services subindices of Borsa Istanbul using the Diebold-Yılmaz connectedness index methodology. The findings indicate that the banks index typically acts as a net receiver of connectedness from industrials and services indices. If the banks index is considered a proxy for the financial side of the Turkish economy while the other two represent the real side, this result aligns with earlier observations on the connectedness between the real and financial sides of economies. Specifically, it suggests that when a proxy for the real side incorporates financial variables, the real side tends to be a net source of connectedness most of the time. As shock propagators, industrials play a dominant role, and the banks index often moves in the opposite direction to the other two sectors.
Key Words: Real and Financial Sectors, Financial Connectedness, Volatility, Borsa Istanbul.
JEL Classification: C32, E44, G10.

Anahtar Kelimeler

real and financial sectors, connectedness, volatility, Borsa Istanbul

Borsa İstanbul Sektörel Bağlanmışlık Analizi

Öz

Bu çalışma, Diebold-Yılmaz bağlanmışlık endeksi metodolojisi kapsamında Borsa İstanbul'un banka, sanayi ve hizmet alt endeksleri arasındaki volatilite bağlanmışlığını incelemektedir. Bulgular, bankalar endeksinin tipik olarak sanayi ve hizmetler endekslerinden net bir bağlanmışlık alıcısı olarak hareket ettiğini göstermektedir. Bankalar endeksinin Türkiye ekonomisinin finansal tarafını, diğer ikisinin ise reel tarafını temsil ettiği düşünülürse, bu sonuç ekonomilerin reel ve finansal tarafları arasındaki bağlanmışlığa ilişkin daha önceki gözlemlerle de uyumludur. Özellikle, reel taraf için kullanılan temsili değişken finansal değişkenleri içerdiğinde, reel tarafın çoğu zaman net bir bağlantılılık kaynağı olma eğiliminde olduğu gözlemlenmektedir. Şok yayıcı olarak, sanayi sektörü baskın bir rol oynamakta ve bankalar endeksi genellikle diğer iki sektörün tersi yönünde hareket etmektedir.
Anahtar Kelimeler: Reel ve Finansal Sektörler, Finansal Bağlanmışlık, Oynaklık, Borsa İstanbul.
JEL sınıflandırması: C32, E44, G10.

Anahtar Kelimeler

reel ve finansal sektörler, bağlanmışlık, oynaklık, Borsa Istanbul

Borsa Istanbul Sectoral Connectedness Analysis

Öz

This paper investigates volatility connectedness between banks, industrials and services subindices of Borsa İstanbul within Diebold-Yılmaz connectedness index methodology. We find that banks index is usually a net connectedness receiver from industrials and services indices. If banks index is considered a proxy for the financial side of the Turkish economy and the other two are deemed to represent the real side, the abovementioned result also confirms one of the earlier findings about connectedness between the real and the financial sides of economies, which mainly states that if a proxy for the real side of the economy is “contaminated” with financial variables; real side is usually a net source of connectedness most of the time. As shock propagators; industrials play a dominant role and banks index move in opposite direction with the other two sectors most of the time.

Anahtar Kelimeler

real and financial sectors, connectedness, volatility, Borsa Istanbul

Kaynakça

• Antonakakis, N., Chatziantoniou, I., and Gabauer, D. (2020). Refined Measures of Dynamic Connectedness Based on Time-varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, Vol. 13, No. 4, 84.
• Bonacich, P. (1987). Power and Centrality: A Family of Measures. American Journal of Sociology. Vol. 92, 1170-1182.
• Berument, H., Akdi, Y., and Atakan, C. (2005). An Empirical Analysis of Istanbul Stock Exchange Sub-Indexes. Studies in Nonlinear Dynamics and Econometrics, Vol. 9, No. 3.
• Chatziantoniou, I., Gabauer, D., and Marfatia, H. A. (2022). Dynamic Connectedness and Spillovers Across Sectors: Evidence from The Indian Stock Market. Scottish Journal of Political Economy, Vol. 69, 283-300.
• Chirila, V. (2022). Connectedness between Sectors: The Case of the Polish Stock Market Before and During COVID-19. Journal of Risk and Financial Management, Vol. 15, 322.
• Costa, A., Matos, P., and da Silva, C. (2022), Sectoral Connectedness: New Evidence From US Stock Market During COVID-19 Pandemics. Finance Research Letters, Vol. 45.
• Diebold, F. X., and Yılmaz, K. (2009). Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets. The Economic Journal, Vol. 119, No. 534, 158-171.
• Diebold, F. X., and Yılmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, Vol. 28, No. 1, 57-66.
• Diebold, F. X., and Yılmaz, K. (2014). On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms. Journal of Financial Econometrics, Vol. 14, No. 1, 81-127.
• Duran, S., and Şahin, A. (2006). İMKB Hizmetler, Mali, Sınai ve Teknoloji Endeksleri Arasındaki İlişkinin Belirlenmesi. Sosyal Bilimler Araştırmaları Dergisi, Vol. 1, 57-70.
• Ekinci, R., and Gençyürek, A. G. (2021). Dynamic Connectedness Between Sector Indices: Evidence from Borsa Istanbul, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, Vol. 16, No. 2, 512-534.
• Eyüboğlu, S., and Eyüboğlu, K. (2019). Testing The Interdependence of Borsa Istanbul Sector Indices. Erciyes University Journal of Faculty of Economic and Administrative Sciences, Vol. 53, 246-260.
• Kamışlı M., and Sevil G. (2018). Borsa İstanbul Alt Sektör Endeksleri Arasındaki Oynaklık Yayılımlarının Analizi. Business and Management Studies: An International Journal, Vol. 6, No. 4, 1015-1032.
• Kocaarslan, B. (2020). Borsa İstanbul (BIST) Teknoloji Endeksi ve Diğer Ana Sektör Endeksleri Arasindaki Volatilite Etkileşimi. Business and Management Studies: An International Journal, Vol. 8, No. 1, 458-475.
• Newman, M.E.J. (2010). Networks: An introduction. New York: Oxford University Press.
• Pesaran, M.H., and Shin, Y. (1998). Generalized Impulse Response Analysis in Linear Multivariate Models. Economics Letters, Vol. 58, 17-29.
• Schmidbauer, H., Roesch, A., and Uluceviz, E. (2013). Market Connectedness: Spillovers, Information Flow, and Relative Market Entropy. Koç University-TUSIAD Economic Research Forum Working Paper, No. 1320, October.
• Schmidbauer, H., Roesch, A., and Uluceviz, E. (2017). Frequency Aspects of Information Transmission in a Network of Three Western Equity Markets. Physica A: Statistical Mechanics and its Applications, Vol. 486, 933-946.
• Schmidbauer, H., Roesch, A., Uluceviz, E., and Erkol, N. (2016). The Russian stock market during the Ukrainian crisis: A network perspective. Czech Journal of Economics and Finance, Vol. 66, No. 6, 478-509.
• Şenol, Z. (2020). Pay Piyasası Sektörleri Arasındaki Oynaklık Yayılımı. Gazi İktisat ve İşletme Dergisi, Vol. 6, No. 3, 257-267.
• Topaloğlu, E. E. (2020). Borsa İstanbul Pay Endekslerinin Volatilite Yapısı ve Volatilite Yayılımı: GARCH ve MGARCH Modelleri ile BIST Sınai ve Mali Endeksleri Örneği. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, Vol. 63, 17-38.
• Uluceviz, E., Yılmaz K. (2020). Real-financial Connectedness in The Swiss Economy. Swiss Journal of Economics and Statistics, Vol. 156, No. 1.
• Uluceviz, E., Yılmaz K. (2021). Measuring Real-financial Connectedness in The U.S. Economy. North American Journal of Economics and Finance, Vol. 58.
• Yin, K., Liu, Z., Jin., X. (2020). Interindustry Volatility Spillover Effects in China’s Stock Market. Physica A: Statistical Mechanics and its Applications, Vol. 539.