Document Type : Research Article
Authors
1 Department of economic and management, Semnan University, Semnan, Iran
2 Department of Mathematics, Faculty of Statistics, Mathematics & Computer, Allameh Tabataba’i University, Tehran, Iran
Abstract
The purpose of this study is to investigate the effects and risk spillover from the global crude oil market on Tehran Stock Exchange Oil Group. For this purpose, we used a combination of copula models and switching models in this research. First, we will examine marginal models and examine Heston switching and Markov switching models in this market. Then we create the multivariate distribution function using Clayton's copula. The data analyzed in this research are related to the global crude oil markets and the Tehran Stock Exchange Oil Group from December 2011 to January 2023. This time period was chosen due to the examination of different regimes in the above markets and also the selection of the appropriate marginal model for these markets. The results show the crude oil market has influenced on Tehran Stock Exchange and also the Tehran Stock Exchange Oil Group indices. Volatility in this global market cause turbulence in the Tehran stock market and this market is affected by the global crude oil market. This is due to the influence of the global crude oil market on total prices in these markets. Heston switching model and its combination with copula models including Clayton copula can bring good results. This is confirmed by comparing this model with other models such as copula Markov switching models.
Keywords
effect on return volatility: A study on stock markets in the Asia-Pacific region, Pac.-Basin
Financ. J., 69 (2021), p. 101653.
[2] Alberto, B.; David, L.T.; Danilo, L.; Marsiglio, S. Financial contagion and economic development: An epidemiological approach, J. Econ. Behav. Organ., 162 (2019), pp. 211228.
[3] Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., De Gracia, F.P., Oil volatility, oil and
gas firms and portfolio diversification, Energy Eco, 70 (2018), pp. 499515.
[4] Arouri, M.E.H., Jouini, J., Nguyen, D.K., On the impacts of oil price fluctuations on
European equity markets: volatility spillover and hedging effectiveness, Energy Econ, 34 (2)
(2012), 611617.
[5] Awartani, B., Maghyereh, A., Dynamic spillovers between oil and stock markets in the Gulf
cooperation council countries, Energy Econ, 36 (2013), pp. 2842.
[6] Azimi,S., Neisy,A., Mohammadi,T., Role of Structural Shocks on Fluctuations of Crude
Oil Prices, Quarterly Journal of Applied Theories of Economics, Vol 6, Issue 1 (2019), pp.
241-264.
[7] Azizi,S., Neisy,A., Mathematic modeling and optimization of bank asset and liability by using
fractional goal programing approach, International journal of modeling and optimization, Vol
7, Issue 2 (2017), pp. 85-91.
[8] Bouri, E., Oil volatility shocks and the stock markets of oil-importing MENA economies: a
tale from the financial crisis, Energy Econ, 51 (2015), pp. 590598.
[9] Bouri, E., Awartani, B., Maghyereh, A., Crude oil prices and sectoral stock returns in Jordan
around the Arab uprisings of 2010, Energy Econ, 56 (2016), pp. 205214.
[10] Bouri, E., Jain, A., Biswal, P.C., Roubaud, D., Cointegration and nonlinear causality
amongst gold, oil, and the Indian stock market: evidence from implied volatility indices,
Resources Policy, 52 (2017), pp. 201206.
[11] Bouri, E., Demirer, R., On the volatility transmission between oil and stock markets: a
comparison of emerging importers and exporters, Econ. Politic., 33 (1) (2016), pp. 6382.
[12] Broadstock, D.C., Filis, G., Oil price shocks and stock market returns: new evidence from
the United States and China. J. Int. Financ. Mark. Inst. Money 33, 417433. Broadstock,
D.C., Cao, H., Zhang, D., 2012. Oil shocks and their impact on energy related stocks in
China, Energy Econ, 34 (6) (2014), pp. 18881895.
[13] Canela, M.A., Collazo, P. , Modelling dependence in Latin American markets using copula
functions. Working Paper, IESE Business School (Barcelona). 2006.
[14] Chang, K.L. Does REIT index hedge inflation risk? new evidence from the tail quantile
dependences of the Markov-switching GRG copula, N. Am. J. Econ. Finance., 39 (2017),
pp. 5667.
[15] Costinot, A., Roncalli, T., & Teiletche, J., Revisiting the dependence between financial
markets with copulas. Working Paper, 2006.
[16] Degiannakis, S., Filis, G., Floros, C., Oil and stock returns: evidence from European industrial sector indices in a time-varying environment, J. Int. Financ. Mark. Inst. Money 26,
(2013), pp. 175191.
[17] Fan, H.C.; Gou, Q.; Peng, Y.C. Spillover effects of capital controls on capital flows and
financial risk contagion, J. Int. Money Finance, 105 (2020), 102189.
[18] Hamma, W., Jarboui, A., Ghorbel, A., Effect of oil price volatility on Tunisian stock market
at sector-level and effectiveness of hedging strategy, Procedia. Finance Eco, 2014.
[19] Hui Ding , Yisu Huang , Jiqian Wang, Have the predictability of oil changed during the
COVID-19 pandemic: Evidence from international stock markets, International Review of
Financial Analysis, Volume 87, (2023), p. 102620.
[20] Huang, J.J.; Lee, K.J.; Liang, H.M.; Lin, W.F. Estimating value at risk of portfolio by
conditional copula-GARCH method, Insure. Math. Econ, 45 (2009), pp. 315324.
[21] Hussain, S.I.; Li, S. The dependence structure between Chinese and other major stock markets using extreme values and copulas, Int. Rev. Econ. Financ., 56 (2018), pp.421437.
[22] Ji, Q., Zhang, D., Geng, J.B., Information linkage, dynamic spillovers in prices and volatility between the carbon and energy markets, J. Clean. Prod, 198 (2018), pp. 972978.
[23] Jin, X., Volatility transmission and volatility impulse response functions among the Greater
China stock markets, J. Asian Econ 39 (2015), pp. 4358
[24] Kang, W., Ratti, R.A., Yoon, K.H., The impact of oil price shocks on the stock market
return and volatility relationship, J. Int. Financ. Mark. Ins, Money 34 (2015), pp. 4154.
[25] Mensi, W., Hammoudeh, S., Shahzad, S.J.H., Shahbaz, M., Modeling systemic risk and
dependence structure between oil and stock markets using a variational mode decompositionbased copula method, J. Bank. Financ., 75 (2017), pp. 258279
[26] Mensi, W., Hammoudeh, S., Shahzad, S.J.H., Shahbaz, M., Modeling systemic risk and
dependence structure between oil and stock markets using a variational mode decompositionbased copula method, J. Bank. Financ., 75 (2017), pp. 258279.
[27] Mihai, N.; Maria, M.P. Time-varying dependence in European equity markets: A contagion
and investor sentiment driven analysis, Econ. Model, 86 (2020), pp. 133147.
[28] Mwamba,J, Mwambi,S ,Assessing Market Risk in BRICS and Oil Markets: An Application
of Markov Switching and Vine Copula, International Journal of Financial Studies, 2021.
[29] Narayan, P.K., Narayan, S., Sharma, S.S., An analysis of commodity markets: what gain for
investors?, J. Bank. Finance 37 (10) (2013), pp. 38783889.
[30] Neisy, A., An Approximation Scheme for Value at Risk under Mean Reverting Stochastic
Volatility Model, Studies of Applied Economics, Vol. 39, Issue 3.
[31] Patton, A.J., Modelling asymmetric exchange rate dependence”, International Economics
Review, 47 (2) (2006), pp. 527- 556.
[32] Patton, Andrew J., On the Out of Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation, Journal of Financial Econometrics, Vol. 2, No. 1 (2004), pp.
130-168.
[33] Peng, C., Zhu, H., Guo, Y., Chen, X., Risk spillover of international crude oil to China’s
firms: evidence from granger causality across quantile, Energy Econ, 72 (2018), pp. 188199.
[34] Peymani,M., Neisi,A., Tehran Stock Exchange Total Index Modeling by Stochastic Differential Equation, Journal of Securities Exchange, vol 8, Issue 30 (2015), pp. 147-168.
[35] Saghafi,R., An Appraisal of Downside and Upside Risk Spillovers of Exchange Rates, Crude
Oil and Gold Prices on Tehran Stock exchange, University of Tabriz Faculty of Economics
and Management Department of Economics, 2018.
[36] Selmi,K , Mensi,W , Hammoudeh,S , Bouoiyour,J , Is Bitcoin a hedge, a safe haven or a
diversifier for oil price movements? A comparison with gold, Energy Economics, Volume 74
(2018), pp. 787-801.
[37] Suleman Sarwar a, Aviral Kumar Tiwari b , Cao Tingqiu, Analyzing volatility spillovers
between oil market and Asian stock markets, Resources Policy, 66 (2020), p. 101608.
[38] Salimi Nasab,S., Neisy, A., A stochastic regime switching model for short-term interest rates
in the Iranian currency market, University of Science and Culture, 2013.
[39] Tansuchat Roengchai, Woraphon Yamaka Kritsana Khemawanit Songsak Sriboonchitta , Analyzing the Contribution of ASEAN Stock Markets to Systemic Risk. Robustness in Econometrics, 2017.
[40] Tiwari,A.K , Trabelsi,N , Alqahtani,F , Raheem,I., ystemic risk spillovers between crude oil
and stock index returns of G7 economies: Conditional value-at-risk and marginal expected
shortfall approaches, Energy Economics, Volume 86, (2020), p. 104646
[41] Tiwari, A.K., Jena, S.K., Mitra, A., Yoon, S.M., Impact of oil price risk on sectoral equity
markets: implications on portfolio management, Energy Econ, 70 (2018), pp. 382395.
[42] Zhang, D., Cao, H., Sectoral responses of the Chinese stock market to international oil shocks.
Emerg. Mark. Financ. Trade, 49 (6) (2013), pp. 3751.
[43] Zhang, D., Shi, M., Shi, X., Oil indexation, market fundamentals, and natural gas prices:
an investigation of the Asian premium in natural gas trade, Energy Econ, 69 (2018), pp.
3341.
[44] Zhang, D., Ji, Q., Kutan, A.M., Dynamic transmission mechanisms in global crude oil prices:
estimation and implications, Energy 175 (2019), pp. 11811193.
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