Analysis of Relationship Between BIST-100 and BIST Sector Indices with VIX Index

Yıl 2018, Cilt: 21 Sayı: 40, 351 - 374, 15.12.2018

Şakir Sakarya Hilmi Tunahan Akkuş

https://doi.org/10.31795/baunsobed.492470

Cited By: 24

Öz

The VIX index is an important index
used as an indicator for estimating future expected movements of capital
markets worldwide. The aim of this study is to determine the causality relation
between the VIX index, the BIST National 100 index and the BIST sectoral indices
(Bank, Financial and Technology) for the period between 05.01.2010-22.06.2018.
ADF and PP unit root tests, ARDL boundary test and Toda-Yamamoto causality test
were used for analysis. According to the cointegration test results, there is a
long and statistically significant relationship between VIX index and BIST
National 100 (XU100), BIST Bank (XBANK), BIST Financial (XUMAL) and BIST
Technology (XUTEK) indices. According to Toda-Yamamoto causality test results,
one-way causality relation was found from VIX index towards XU100, XBANK, XUMAL
and XUTEK indices.

Anahtar Kelimeler

VIX Index, ARDL Boundary Testing, Toda-Yamamoto Causality Test

BİST-100 VE BİST SEKTÖR ENDEKSLERİ İLE VIX ENDEKSİ ARASINDAKİ İLİŞKİSİNİN ANALİZİ

Öz

VIX endeksi, tüm dünyada menkul kıymet piyasalarının
gelecekteki beklenen hareketlerinin tahmini için gösterge olarak kullanılan
önemli bir endekstir. Bu çalışmanın amacı, 05.01.2010-22.06.2018 tarihleri
arasındaki dönem için VIX endeksi ile BİST Ulusal 100 endeksi ve BİST sektörel
endeksler (Banka, Mali ve Teknoloji) arasındaki nedensellik ilişkisinin tespit
edilmesidir. Analiz yöntemleri olarak ADF ve PP birim kök testleri, ARDL sınır
testi ve Toda-Yamamoto nedensellik testi kullanılmıştır. Çalışmadan elde edilen
eşbütünleşme testi sonuçlarına göre, VIX endeksi ile BİST Ulusal 100 (XU100),
BİST Banka (XBANK), BİST Mali (XUMAL) ve BİST Teknoloji (XUTEK) endeksleri
arasında uzun dönemli istatistiksel olarak anlamlı bir ilişki bulunmaktadır.
Toda-Yamamoto nedensellik testi sonuçlarına göre ise, VIX endeksinden XU100,
XBANK, XUMAL ve XUTEK endekslerine doğru tek yönlü nedensellik ilişkisi
bulunmuştur.

Anahtar Kelimeler

VIX Endeksi, ARDL Sınır Testi, Toda-Yamamoto Nedensellik Testi

Kaynakça

• Banerjee, A. ve Kumar, R. (2011). Realized Volatility and India VIX. Working Paper, Indian Institute of Management Calcutta, No. 688. Becker, R., Clements, A. E. ve McClelland, A. (2009). The Jump Component of S&P 500 Volatility and the VIX Index. Journal of Banking & Finance, 33 (6) 1033-1038. CBOE (2018). Chicago Board of Exchange. 25.06.2018 tarihinde http://www.cboe.com/products/vix-index-volatility/vix-options-and-futures/vix-index/vix-historical-data adresinden erişildi. Corrado, C. J. ve Miller, J. T. W. (2005). The Forecast Quality of CBOE Implied Volatility Indexes. Journal of Futures Markets, 25 (4), 339-373. Çil Yavuz, N. (2015). Finansal Ekonometri. Der Yayınları, İstanbul. Dickey, D. A. ve Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with A Unit Root. Econometrica, 49(4), 1057-1072). Dikmen, N. (2012). Ekonometri: Temel Kavramlar ve Uygulamalar. Bursa: Dora Yayıncılık. Emna, R. ve Myriam, C. (2017). Dynamics of the Relationship between Implied Volatility Indices and Stock Prices Indices: The Case of European Stock Markets. Asian Economic and Financial Review, 7 (1), 52-62. Engle, R. F. ve Granger, C. W. J. (1987). Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica, 55 (2), 251-276. Erdoğdu, H. ve Baykut, E. (2016). BIST Banka Endeksi’nin (XBANK) VIX ve MOVE Endeksleri ile İlişkisinin Analizi. Bankacılar Dergisi, 98, 57-72. Fernandes, M., Medeiros, M. C. ve Scharth, M. (2013). Modeling and Predicting the CBOE Market Volatility Index. Sao Paulo Schools of Economics, Working Paper 342, Ceqef No: 10. Giot, P. (2005). On the Relationships between Implied Volatility Indices and Stock Index Returns. The Journal of Portfolio Management, 31(3), 92-100. Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrica, 37 (3), 424-438. Gujarati, D. (2015). Örneklerle Ekonometri (N. Bolatoğlu, Çev.). Ankara: BB101 Yayınları. İskenderoğlu, Ö. ve Akdağ, S. (2018). VIX Korku Endeksi ile Çeşitli Ülkelerin Hisse Senedi Endeks Getirileri Arasında Bir Nedensellik Analizi. 2. International Economic Research and Financial Markets Congress: 12-13-14 Nisan 2018 – Cappadocia: Bildiriler (489-505). Johansen, S. (1988). Statistical Analysis of Cointegrating Vectors. Journal of Economic Dynamics and Control, 12 (2-3), 231-254. Jung, Y. (2016). Relative Performance of VIXC vs. GARCH in Predicting Realized Volatility Changes. Investment Analyst Journal, 45 (1), 1-16. Kaya, A. ve Çoşkun, A. (2015). VIX Endeksi Menkul Kıymet Piyasalarının Bir Nedeni Midir? Borsa İstanbul Örneği. C.Ü. İktisadi ve İdari Bilimler Dergisi, 16 ( 1), 175-186. Kaya, A., Güngör, B. ve Özçomak, M. S. (2014). Is VIX Indeks a Fear Indeks for Investors? OECD Countries Stock Exchange Example with ARDL Approach. Proceedings of the First Middle East Conference on Global Business, Economics, Finance and Banking (ME14 DUBAI Conference) Dubai, 10-12 October 2014. Kaya, E. (2015). Borsa İstanbul (BIST) 100 Endeksi ile Zımni Volatilite (VIX) Endeksi Arasındaki Eş-Bütünleşme ve Granger Nedensellik. KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi, 17 (28), 1-6. Konstantinidi, E, Skiadopoulos, G ve Tzagkaraki, E. (2008). Can The Evolution of Implied Volatility Be Forecasted? Evidence from European and US Implied Volatility Indices. Journal of Banking & Finance, 32 (11), 2401-2411. Korkmaz, T. ve Çevik, E. İ. (2009). Zımni Volatilite Endeksinden Gelişmekte Olan Piyasalara Yönelik Volatilite Yayılma Etkisi. BDDK Bankacılık ve Finansal Piyasalar Dergisi, 3 (2), 87-105. Kula, V. ve Baykut, E. (2017). Borsa İstanbul Kurumsal Yönetim Endeksi (XKURY) İle Korku Endeksi (Chicago Board Options Exchange Volatility Index-VIX) Arasındaki İlişkinin Analizi. AKÜ İktisadi ve İdari Bilimler Fakültesi Dergisi, 19 (2), 27-37. Lahrech, A. ve Sylwester, K. (2011). U.S. and Latin American Stock Market Linkages. Journal of International Money and Finance, 30 (7), 1341-1357. Lee, B. S. ve Ryu, D. (2013). Stock Returns and Implied Volatility: A New VAR Approach. Economics E-Journal, 7 (3), 1-20. MacKinnon, J. G. (1996). Numerical Distribution Functions for Unit Root and Cointegration Tests. Journal of Applied Econometrics, 11 (6), 601-618. Ozair, M. (2014). What does the VIX Actually Measure: An Analysis of the Causation of SPX and VIX. ACRN Journal of Finance and Risk Perspectives, 3 (2), 83-132. Ozdemir, Z. A., Olgun, H. ve Saracoglu, B. (2009). Dynamic Linkages between The Center and Periphery in International Stock Markets. Research in International Business and Finance, 23 (1), 46-53. Pesaran, M. H., Shin, Y. ve Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationship. Journal of Applied Econometrics, 16 (3), 289-326. Phillips, P. C. B. ve Ouliaris, S. (1990). Asymptotic Properties of Residual Based Tests for Cointegration. Econometrica, 58 (1), 165-193. Phillips, P. C. B. ve Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Econometrica, 75 (2), 335-346. Poon, S-H. ve Granger, C. W. J. (2003). Forecasting Volatility in Financial Markets: A Review. Journal of Economic Literature, 41 (2), 478-539. Sarwar, G. ve Khan, W. (2017). The Effect of US Stock Market Uncertainty on Emerging Market Returns. Emerging Markets Finance and Trade, 53 (8), 1796-1811. Sevüktekin, M. ve Çınar, M. (2014). Ekonometrik Zaman Serileri Analizi: Eviews Uygulamalı. Bursa: Dora Yayıncılık. Shaikh, I. ve Padhi, P. (2014). The Implied Volatility Index_Is ‘investor fear gauge’ or ‘forward-looking’?. Borsa İstanbul Review, 15 (1), 44-52. Tarı, R. (2014). Ekonometri. Kocaeli: Umuttepe Yayınları. Toda, H. Y. ve Yamamoto, T. (1995). Statistical Inference in Vector Autoregressions with Possibly Integrated Processes. Journal of Econometrics, 66 (1-2), 225-250.