The Causality Relationship Among Stock Markets In Risk Situation

Year 2022, , 2023 - 2042, 19.10.2022

Serhat Sezen , Emrah İsmail Çevik

https://doi.org/10.21547/jss.1137227

Abstract

In this paper, it is aimed to determine the possible existence of a causal relationship among the stock markets of the G-20 countries in extreme risk situations. For this purpose, between January 2, 1995 and May 26, 2022, using daily closing prices, the possible existence of extreme risk situations in the stock markets of G-20 countries was investigated with the risk situation causality test developed by Hong et al., (2009). According to the causality test results, it is unidirectional from the USA, Italy, Germany, France, China, Brazil, Argentina and India stock markets to the Turkish stock market and from the Turkish stock market to the Indonesia, Mexico and South African stock markets; It has been determined that there is a causal relationship between the stock markets of Japan, Canada, Australia, Korea and Russia and the Turkish stock market in case of bidirectional risk. Finally, no causal relationship was found in any risk situation with the UK stock market.

Keywords

Stock Markets, GARCH Models, Hong Causality Test

Hisse Senedi Piyasaları Arasında Risk Durumunda Nedensellik İlişkisi

Abstract

Bu çalışmada, G-20 ülkelerinin hisse senedi piyasaları arasında aşırı risk durumlarında nedensellik ilişkisinin olası varlığının tespit edilmesi amaçlanmıştır. Bu amaçla 2 Ocak 1995-26 Mayıs 2022 tarihleri arasında günlük hisse senedi kapanış fiyatları kullanılarak, G-20 ülkelerinin hisse senedi piyasaları arasında aşırı risk durumlarının olası varlığı Hong vd., (2009) tarafından geliştirilen risk durumunda nedensellik testi ile araştırılmıştır. Nedensellik testi sonuçlarına göre, ABD, İtalya, Almanya, Fransa, Çin, Brezilya, Arjantin ve Hindistan hisse senedi piyasalarından Türkiye hisse senedi piyasasına doğru ve Türkiye hisse senedi piyasasından da Endonezya, Meksika ve Güney Afrika hisse senedi piyasalarına doğru tek yönlü; Japonya, Kanada, Avustralya, Kore ve Rusya hisse senedi piyasaları ile Türkiye hisse senedi piyasası arasında çift yönlü risk durumunda nedensellik ilişkisi olduğu tespit edilmiştir. Son olarak, İngiltere hisse senedi piyasası ile herhangi bir risk durumunda nedensellik ilişkisine rastlanılmamıştır.

Keywords

Hisse Senedi Piyasaları, GARCH Modeller, Hong Nedensellik Testi

References

• Ağırman, E., Bozma, G., & Ahmid, A. B. (2018). The volatility spillovers between Turkey and North Africa (ETM) stock markets: VARMA-BEKK GARCH model. MANAS Sosyal Araştırmalar Dergisi, 7(4), 181-191.
• Alfreedi, A. A. (2019). Shocks and Volatility Spillover Between Stock Markets of Developed Countries and GCC Stock Markets. Journal of Taibah University for Science, 13(1), 112-120.
• Badhani, K. N. (2009). Response Asymmetry in Return and Volatility Spillover from the US to Indian Stock Market. The IUPJournal of Applied Finance, 15(9), 22-45.
• Bali, T.G. (2000). Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate. Journal of Financial and Quantitative Analysis, 35, 191-215.
• Choudhry, T. (2004). International Transmission of Stock Returns and Volatility: Empirical Comparison Between Friends and Foes. Emerging Markets Finance and Trade, 40(4), 33–52.
• Çelik, İ., Özdemir, A., & Demir-Gülbahar, S. (2018). Gelişmekte Olan Ülkelerde Getiri ve Volatilite Yayılımı: NIMPT Ülkelerinde VAR-EGARCH Uygulaması. Finans Politik & Ekonomik Yorumlar, 55(636), 9-24.
• Çevik, E. İ. (2017). Pay Piyasası ile Döviz Kurları Arasında Risk Durumlarında Nedensellik İlişkisi. Balkan Sosyal Bilimler Dergisi, 6(12), 82-94.
• Değirmenci, N., & Abdioğlu, Z. (2017). Finansal Piyasalar Arasındaki Oynaklık Yayılımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 54, 104-125.
• Fujii, E. (2005). Intra and Inter regional Causal Linkages of Emerging Stock Markets: Evidence from Asia and Latin America in and out of Crises. Journal of International Financial Markets, Institutions and Money, 15, 315-342.
• Hong, Y., Li, H., & Zhao, F. (2004). Out-of-Sample Performance of Discrete-Time Short-Term Interest Models. Journal of Business and Economic Statistics, 22(4), 457–473.
• Hong, Y., Li, H., & Zhao, F. (2007). Can the Random Walk Model Be Beaten in Out-Of-Sample Density Forecasts? Evidence From Intraday Foreign Exchange Rates. Journal of Econometrics, 141(2), 736-776.
• Hong, Y., Liu, Y., & Wang, S. (2009). Granger Causalıty in Risk and Detection of Extreme Risk Spillover Between Financial Markets. Journal of Econometrics, 150, 271-287.
• Inclan, C., & Tiao, G. (1994). Use of Cumulative Sums of Squares Retrospective Detection of Changes in Variance. Journal of the American Statistic Association, 89, 913-923.
• Ke, J., Wang, L., & Murray, L. (2010). An empirical analysis of the volatility spillover effect between primary stock markets abroad and China. Journal of Chinese Economic and Business Studies, 8(3), 315-333.
• Kumar, A. (2019). Shock and Volatility Spillovers between Stock Markets of India and Select Asian Economies. Review of Professional Management, 17(1), 46-57.
• 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.
• Longin, F.M. (2000). From Value at Risk to Stress Testing: The Extreme Value Approach. Journal of Banking and Finance, 24(7), 1097–1130.
• Neaime, S. (2012). The Global Financial Crisis, Financial Linkages and Correlations In Returns and Volatilities In Emerging MENA Stock Markets. Emerging Markets Review, 13, 268–282.
• Nikmanesh, L., Nor, A.H.S.M., Sarmidi, T., & Janor, H. (2014). Return and Volatility Spillovers Between the US, Japanese and Malaysian Stock Markets. Jurnal Pengurusan, 41, 101-111.
• Sanso, A., Arago, V., & Carrion, J. L. (2004). Testing for Change in the Unconditional Variance of Financial Time Series. Revista de Economia Financiera, 4, 32-53.
• Singh, P., Kumar, B., & Pandey, A. (2010). Price and volatility spillovers across North American, European and Asian stock markets. International Review of Financial Analysis, 19, 55-64.
• Taşdemir, M., & Yalama, A. (2014). Volatility Spillover Effects in Interregional Equity Markets: Empirical Evidence from Brazil and Turkey. Emerging Markets Finance & Trade, 50(2), 190-202.
• Theodossiou, P., Kahya, E., Koutmos G., & Christofi, A. (1997). Volatility Reversion and Correlation Structure of Returns in Major International Stock Markets. The Financial Review, 32(2), 205-224.
• Toraman, C., İğde, M., Buğan, M. F., & Kılıç, Y. (2016). Volatility Spillover Effect from Conventional Stock Markets to Islamic Stock Markets. International Journal of Academic Research in Economics and Management Sciences, 5(4), 264-281.
• Verardi, V., & Vermandele, C. (2018). Univariate and multivariate outlier identification for skewed or heavy-tailed distributions. The Stata Journal, 18(3), 517-532.
• Warshaw, E. (2020). Asymmetric Volatility Spillover Between European Equity and Foreign Exchange Markets: Evidence from The Frequency Domain. International Review of Economics & Finance, 68, 1-14.