Providing a Network for Measuring the Dynamics Volatility Connectedness of Oil and Financial Markets
Subject Areas : Complex Networks
Nasser Gholami
1
(Allameh Tabataba‟i University)
Teymor Mohammadi
2
(Allameh Tabataba‟i University)
Hamid Amadeh
3
(Allameh Tabataba‟i University,)
Morteza Khorsandi
4
(Allameh Tabataba‟i University)
Keywords: Oil Markets , System Design , Volatility , Variance Decomposition Approach , Dynamics Connectedness , Network,
Abstract :
Various studies have shown that markets are not separated and that fluctuations in different markets affect each other. Therefore, awareness of connectedness is needed for investors and policymakers for making appropriate decisions. The aim of this paper is to measure the dynamics connectedness of selected stock markets in the Middle East, oil markets, gold, the dollar index, and euro-dollar and pound-dollar exchange rates during the period February 2007 to August 2019 in networks with different weekly horizons. In this paper, we intend to evaluate the pairwise impact of crude oil and the Middle East stock markets, in particular on the Tehran Stock Exchange, and to analyze this variance using different time horizons. The results show that in all time horizons the variance of forecast error in most markets is due to the shocks themselves. The Saudi Arabian Stock Exchange has the most impact on other Middle Eastern stocks. The dynamics connectedness of the oil markets is remarkable, however, as the time horizon increases, dynamic connectedness between the two markets decreases and they are mostly affected by other markets, especially the Middle East stock exchanges except for Iran. Moreover, Iran stock market is an isolated market. About the gold market, there is a significant connectedness with the pound-dollar exchange rate and gold market; however, the dynamics connectedness of this market with other markets are not significant. Therefore, this market and Iran stock exchange can be used as a tool to hedge risk for investors.
[1] Hamilton, J. D." What is an oil shock?". Journal of econometrics, 113(2), 363-398. 2003.
[2] Kilian, L. "The economic effects of energy price shocks". Journal of Economic Literature, 46(4), 871-909. 2008.
[3] Bagheri, E., & Ebrahimi, S. B., “Estimating Network Connectedness of Financial Markets and Commodities”. Journal of Systems Science and Systems Engineering, 29(5), 572-589. 2020.
[4] Diebold, F. X., & Yılmaz, K. “On the network topology of variance decompositions: Measuring the connectedness of financial firms”. Journal of Econometrics, 182(1), 119-134. 2014.
[5] Billio, M. A.W., and Pelizzon, L. “Econometric measures of connectedness and systemic risk in the finance and insurance sectors”. Journal of financial economics, 104(3), pp. 535-559. 2012.
[6] Acharya, V. Philippon, T., & Richardson, M. “Measuring systemic risk”. Review of Financial Studies, 30(1), pp. 2–47. 2017.
[7] Adrian, T. “CoVaR”. The American Economic Review, 106(7), pp. 1705-1741. 2016.
[8] Jahangiri, Khalil and Hekmati Farid, Samad. “Studying the effects of spillover volatility on stock markets, gold, oil and foreign exchange”. Journal of Economic Research, p. 194-161. 2015. (In Persian).
[9] Maghyereh, A. I., Awartani, B., & Bouri, E. “The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes”. Energy Economics, 57, 78-93. 2016.
[10] Mimipour, Sayab and Feli, Atefeh. “Investigation of spillover volatility of oil prices on yields of selected industries in Tehran Stock Exchange: variance decomposition approach”. Monetary Economics Research. 2017. (In Persian).
[11] Singh, V. K., Nishant, S., & Kumar, P. “Dynamic and directional network connectedness of crude oil and currencies: Evidence from implied volatility”. Energy Economics, 76, 48-63. 2018.
[12] Husain, S., Tiwari, A. K., Sohag, K., & Shahbaz, M. “Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA”. Resources Policy, 62, 57-65. 2019.
[13] Al-Yahyaee, K. H., Mensi, W., Sensoy, A., & Kang, S. H. “Energy, precious metals, and GCC stock markets: Is there any risk spillover?”. Pacific-Basin Finance Journal, 56, 45-70. 2019.
[14] Fasanya, I., & Akinbowale, S. “Modelling the return and volatility spillovers of crude oil and food prices in Nigeria”. Energy, 169, 186-205. 2019.
[15] Yoon, S. M., Al Mamun, M., Uddin, G. S., & Kang, S. H. “Network connectedness and net spillover between financial and commodity markets”. The North American Journal of Economics and Finance, 48, 801-818. 2019.
[16] Parkinson, M. “The extreme value method for estimating the variance of the rate of return”. Journal of business, 61-65. 1980.
[17] Koop, G., Pesaran, M. H., & Potter, S. M. “Impulse response analysis in nonlinear multivariate models”. Journal of econometrics, 74(1), 119-147. 1996.
[18] Pesaran, H. H., & Shin, Y. “Generalized impulse response analysis in linear multivariate models”. Economics letters, 58(1), 17-29. 1998.