Modeling the measurement of volatility connectedness at the time of the corona outbreak in the structure of the Tehran Stock Exchange industries

Document Type : Original Article

Author

management faculty,payamenoor university,tehran,iran

Abstract

The present study has examined the relationship between the turbulence of the structures of important industries of the Tehran Stock Exchange during the last twelve years using the daily turbulence of the index values of each industry. Using the volatility model based on the analysis of variance approach, the effects of risk spillover due to the occurrence of corona on the stability of twenty important and major industries in the Iranian stock market were measured and evaluated.

Empirical findings showed that the twenty industries studied had little dependence before the corona and the occurrence of Covid 19 had significant effects on the dynamics of turbulence in the industrial structure and the correlation of turbulence reached its maximum during the corona. The most important industries of the Iranian capital market, including chemicals, basic metals, and cement, have the highest impact during this period, and the important role of large industries in propagating turbulence shocks is significant due to their strong internal dependence during extreme events.

Medium and small industries have also increased system turbulence at the time of the corona. Overall, in the pre-Covid 19 era, there were ten risk-taking industries and ten risk-issuing industries, while in the Corona era, thirteen were the risk-issuing industries and seven were the turbulent industries.

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ابراهیمی سرو علیا، محمدحسن، تملکی، حسین. (1399). بررسی سرایت‌پذیری ریسک نکول بین شرکت‌های هلدینگ و شرکت‌های فرعی آن‌ها (موردمطالعه: شرکت گسترش سرمایه‌گذاری ایران‌خودرو ). چشم‌انداز مدیریت مالی،  10(30)، 120-99.
شکری، نعیم، سحاب خدامرادی، مرتضی، حاجیلو مقدم، امیرحسین. (1400). بررسی اثرات سرریز نوسانات مالی میان ارزهای دیجیتالی کاربرد رهیافت گارچ چند متغیره BEKK-GARCH . چشم‌انداز مدیریت مالی، 11(35).
خیابانی، ناصر. محمدیان نیک‌پی، احسان (1397). «تحلیل ریسک سیستمی در صنایع منتخب بورس اوراق بهادار تهران: یک رویکرد رگرسیون چندکی چندمتغیره». فصلنامه پژوهش‌های اقتصادی ایران، شماره 77. صفحه 36-1.
غلامی، ناصر. محمدی، تیمور. قاسمی، عبدالرسول(1399). طراحی مدلی برای سنجش پویایی ارتباطات تلاطمات بورس اوراق  بهادار تهران و بازارهای جهانی»، فصلنامه مدل‌سازی اقتصادی، شماره 1(49)، صفحه 71-49.
نمکی، علی. عباسیان، عزت اله. شفیعی، الهه. (1401). «تجزیه‌وتحلیل میزان ریسک سیستمی شرکت‌های بورس اوراق بهادار تهران با استفاده از رویکرد سیستم‌های پیچیده»، فصلنامه راهبرد مدیریت مالی. 10(1).
Acharya, V. V., Pedersen, L. H., Philippon, T., & Richardson, M. (2017). Measuring systemic risk. The Review of Financial Studies, 30(1), 2–47.
Adrian, T., & Brunnermeier, M. K. (2016). CoVaR. The American Economic Review, 106(7), 1705.
Aldasoro, I., Huang, W., & Kemp, E. (2020). Cross-border links between banks and non-bank financial institutions. BIS Quarterly Review, 61.
Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & De Gracia, F. P. (2018). Oil volatility, oil and gas firms and portfolio diversification. Energy Economics, 70, 499–515.
Billio, M., Getmansky, M., Lo, A. W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535–559.
Corbet, S., Hou, Y., Hu, Y., Lucey, B., & Oxley, L. (2021). Aye corona! the contagion effects of being named corona during the COVID-19 pandemic. Finance Research Letters, 38, 101591
Diebold, F. X., & Yılmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66.
Demirer, M., Diebold, F. X., Liu, L., & Yilmaz, K. (2018). Estimating global bank network connectedness. Journal of Applied Econometrics, 33(1), 1–15.
Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182 (1), 119–134.
Diebold, F. X., & Yilmaz, K. (2015). Trans-atlantic equity volatility connectedness: US and European financial institutions, 2004–2014. Journal of Financial Econometrics, 14(1), 81–127.
Ebrahimi Sarv Oliya, M., Tamalloki, H. (2020). The Spillover Effects of Default Risk between Holding Companies and Their Subsidiaries (Case Study: Iran Khodro Investment Development Co.). ـ Journal of Financial Management Perspective, 10(30), 99-120. (In Persian)
Foglia, M., & Angelini, E. (2020a). The diabolical sovereigns/banks risk loop: A var quantile design. The Journal of Economic Asymmetries, 21, e00158.
Foglia, M., & Angelini, E. (2020b). From me to you: Measuring connectedness between Eurozone financial institutions. Research in International Business and Finance, 101238.
Foglia, M., & Angelini, E. (2020c). The triple (t3) dimension of systemic risk: Identifying systemically important banks in Eurozone. International Journal of Finance & Economics.
Geng, J.-B., Du, Y.-J., Ji, Q., & Zhang, D. (2020). Modeling return and volatility spillover networks of global new energy companies. Renewable and Sustainable Energy Reviews, 135, 110214.
Gholami, N., Mohammadi, T., ghasemi, A. (2020). Design a Model for Measuring the Dynamics Volatility Connectedness of Tehran Stock Exchange and Global Markets. Economical Modeling, 14(49), 49-71.(In Persian)
Gong, X., Liu, Y., & Wang, X. (2021). Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method. International Review of Financial Analysis, 101790.
Goodell, J. W. (2020). COVID-19 and finance: Agendas for future research. Finance Research Letters, 101512
Hardle, W. K., Wang, W., & Yu, L. (2016). Tenet: Tail-event driven network risk. Journal of Econometrics, 192(2), 499–513.
Hautsch, N., Schaumburg, J., & Schienle, M. (2015). Financial network systemic risk contributions. Review of Finance, 19(2), 685–738.
Hernandez, J. A., Kang, S. H., Shahzad, S. J. H., & Yoon, S.-M. (2020). Spillovers and diversification potential of bank equity returns from developed and emerging America. The North American Journal of Economics and Finance, 101219.
Hung, N. T., & Vo, X. V. (2021). Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak. International Review of Financial Analysis, 76, 101730.
Khiabani, N., mohammadian nikpey, E. (2018). Systemic Risk Analysis in Selected Industries of Tehran Stock Exchange: A Multivariate Quantile Regression Approach. Iranian Journal of Economic Research, 23(77), 1-36. (In Persian)
Keddad, B., & Schalck, C. (2020). Evaluating sovereign risk spillovers on domestic banks during the European debt crisis. Economic Modelling, 88, 356–375.
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147.
Namaki, A., Abbasian, E., Shafiei, E. (2022). Analyzing of Systemic Risk Contributions of Tehran Stock Exchange Companies by Complexity Approach. Financial Management Strategy, 10(1).(In Persian)
Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29.
Rizwan, M. S., Ahmad, G., & Ashraf, D. (2020). Systemic risk: The impact of COVID-19. Finance Research Letters, 36.
Shokri, N., Sahab Khodamoradi, M., Hajiloo moghadam, A. (2021). Investigating the effects of financial volatility spillover between digital currencies (application of multivariate GARCH approach). ـ Journal of Financial Management Perspective, 11(35), 143-172. (In Persian)
Wang, G.-J., Xie, C., He, K., & Stanley, H. E. (2017). Extreme risk spillover network: Application to financial institutions. Quantitative Finance, 17(9), 1417–1433.
Wang, G.-J., Xie, C., Zhao, L., & Jiang, Z.-Q. (2018). Volatility connectedness in the chinese banking system: Do state-owned commercial banks contribute more Journal of International Financial Markets, Institutions and Money, 57, 205–230.