Spillover between Tehran Stock Exchange and International Oil Market

Document Type : Research Paper


1 Ph.D. Candidate, Department of Financial Management, Kish International Campus, University of Tehran, Kish, Iran.

2 Assistant Prof., Department of Social and Behavioral Sciences, Kish International Campus, University of Tehran, Kish, Iran.

3 Assistant Prof., Faculty of Industrial Engineering & Management, Shahrood University of Technology, Shahrood, Iran.


Objective: Financial spillovers are commonly defined as occurrences where fluctuations in the price of an asset in one country (or region) trigger changes in the prices of the same asset or other assets in another country (or region). Our country's economy, since the discovery of oil in it; has always relied on this product. It is common among stock market participants that the price of this product fluctuates; it causes fluctuations in the stock market. The present article seeks to investigate the existence of spillover between the Tehran Stock Exchange and the oil market.
Methods: Using daily data on daily returns on the Tehran Stock Exchange index and West Texas Intermediate oil prices during the period December 5, 2008, to November 4, 2019, and the vector autoregressive model we examined spillover between the two markets. This article also examines the Granger causality test between the two markets.
Results: After performing the augmented Dickey-Fuller test and ensuring the stationary of both time-series data; the vector autoregressive model was estimated. Length of optimal lags; With regard to the Akaike information criteria; was determined seven days. According to the results of this article, there is no spillover between the two markets and oil and the stock market are no other cause of fluctuation. In the time series returns on the index; everyday return has a significant relationship with a return of one day; two days; three days; five days and seven days ago. Oil returns have no significant relationship with their amount in any of the previous seven days except the previous day. According to the Granger causality test, the p-value (prob.) in both directions was more than 5%, and therefore the return on oil and the index are not the other cause of the Granger test. Also based on the impulse response function (IRF); the shock to the index and oil returns decays after twelve and eight days, respectively.
Conclusion: Contrary to what was expected; there is no spillover between the two markets. As a result, other factors are involved in changing prices and causing stock market shocks.


Ang, A., Bekaert, G. (2002). International asset allocation with regime shifts. The Review of Financial Studies, 15(4), 1137–1187.
Antoniou, A., Pescetto, G.M., Stevens, I. (2007). Market-wide and sectoral integration: evidence from the UK, USA and Europe. Managerial Finance, 33(3), 173–194.
Brooks, Ch. (2008). Introductory Econometrics for Finance (Second edition). Cambridge University Press.
Capiello, L., Engle, R.F., Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537–572.
Chiang, T.C., Jeon, B.N., Li, H. (2007). Dynamic correlation analysis of financial contagion: evidence from Asian markets. Journal of International Money and Financ, 26(7), 1206–1228.
Creti, A., Joëts, M., Mignon, V. (2013). On the links between stock and commodity markets volatility. Energy Economics37, 16–28.
Diebold, F.X., Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal, Royal Economic Society, 119(534), 158-171.
Diebold, F.X., Yilmaz, K. (2012). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66.
Driessen, J., Laeven, L. (2007). International portfolio diversification benefits: cross country evidence from a local perspective. Journal of Banking & Finance, 31(6), 1693–1712.
Errunza, V., Hogan, K., Hung, M.W. (1999). Can the gains from international diversification be achieved without trading abroad?  Journal of Finance & Accounting, 54(6), 2075–2107.
Eyvazlu, R., Bajalan, S. and Chaharrah, M. (2018). Dynamic survey of the relationship between gold and crude oil’s price uncertainty with banks stock index -method of state space. Financial Engineering and Portfolio Management, 9(36), 31-49. (in Persian)
Hil, R., Carter, Griffiths, William, E., Lim, Guay, C. (2011). Principles of Econometrics, John Wiley & Sons, Inc.
Kang, S.H., Mclver, R., Yoon, S.M. (2017). Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets. Energy Economics, 62, 19–32.
Longin, F., Solnik, B. (1995). Is the correlation in international equity returns constant: 1960-1990? Journal of International Money and Finance, 14(1), 3-26.
Longin, F., Solnik, B. (2001). Extreme correlation and international equity markets. The Journal of Finance, 56(2), 649-676.
Mamipour, S. and Feli, A. (2017). The Impact of Oil Price Volatility on Tehran Stock Market at Sector-Level: A Variance Decomposition Approach. Monetary & Financial Economics, 24(14), 205- 234. (in Persian)
Markwat, T., Kole, E., Van Dijk, D. (2009). Contagion as a domino effect in global stock markets. Journal of Banking & Finance, 33(11), 1996-2012.
Mensi, W., Hammoudeh, S., Shahzad, S.J.H., Shahbaz, M. (2017). Modeling systemic risk and dependence structure between oil and stock markets using a variation mode decomposition-based copula method. Journal of Banking & Finance, 75(C), 258-279.
Ntantamis, C., Zhou, J. (2015). Bull and bear markets in commodity prices and commodity stocks: is there a relation? Resources Policy, 43, 61-81.
Olson, E., Vivian, A.J., Wohar, M.E. (2014). The relationship between energy and equity markets: evidence from volatility impulse response functions. Energy Economics, 43(C), 297-305.
Sadorsky, P. (2014). Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat. Energy Economics, 43, 72–81.
Seyedhosseini, S.M., Ebrahimi, S.B. (2012). Comparing of Volatility Transmission Model with Consideration of Long Memory Effect; Case Study: Three Selected Industry Index. Financial Research Journal, 15(1), 51- 74. (in Persian)
Shahverdi, F. (2017). Investigating the overflow of fluctuations between oil prices and stock price indices in Iran. Master Thesis. Tehran, Alzahra University. (in Persian)
Sharif Karimi, M., Heydarian, M. and Dehghan Jabbarabadi, Sh. (2018). An Analysis of Spillover effects between oil and Tehran Stock Exchange markets during multi-scales, using a wavelet-based VAR-GARCH-Bekk model. Financial Economics, 12(42), 25-46. (in Persian)
Xu, W., Ma, F., Chen, W., Zhang, B. (2019). Asymmetric volatility spillovers between oil and stock markets: evidence from China and the United States. Energy Economics, 80, 310–320.
Yoon, S.M., Mamun, M., Uddin, G.S., Kang, S.H. (2019). Network connectedness and net spillover between financial and commodity markets. The North American Journal of Economics and Finance, Elsevier, 48(C), 801-818.
You, L., Daigler, R.T. (2010). Is international diversification really beneficial? Journal of Banking & Finance, 34(1), 163- 173.
Zhang, D. (2017). Oil shocks and stock markets revisited: measuring connectedness from a global perspective. Energy Economics, 62, 323–333.