Modeling Energy and Steel Price Volatility and Experimental Test of Inter-Market Volatility Spillover: A Multivariate Study Using VECM and Familty GARCH Models

Advances in Mathematical Finance and Applications

مقاله 13، دوره 8، شماره 2، مرداد 2023، صفحه 569-587   

نوع مقاله: َApplied-Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2022.1932695.1605

نویسندگان

Seyed Abdolhamid Bahreini¹؛ Hossein Badiei^{* 2}؛ Faegh Ahmadi³؛ Jahanbakhsh Asadnia⁴

¹Department of Accounting, Qeshm International Branch, Islamic Azad University, Hormozgan, Iran

²Department of Accounting, Faculty of Economics and Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran

³Department of Accounting and Financial Management, Islamic Azad University, Qeshm International Branch, ,Hormozgan, Iran

⁴Invited lecturer Department of Accounting and Financial Management, Islamic Azad University, Qeshm International Branch, ,Hormozgan, Iran

چکیده

The spread of volatility between financial indices indicates the process of information transfer between markets. Despite the relationship between financial markets, the information created in one market can affect other markets as well. Therefore, the main purpose of this study is to investigate the volatility of energy and steel prices and the experimental test of inter-market volatility spillover. To do this, the monthly data of steel and energy price (oil and gas) during 2009 to 2019 were collected from valid databank using VECM and GARCH Family and VAR model and ICSS algorithm were analyzed by considering and without considering structural failure.
Then, the causal relationship between them is examined through Granger causality test. The results show that there is volatility in the energy market (oil and gas) as well as the steel market during the studied time period. Results also show that the price of steel as well as its return and index are changed significantly by energy price effect. However, there is a causal link between energy prices and steel products and these results are consistent with the theoretical basics of the study and review of literature.

کلیدواژه‌ها

Energy and steel price volatility؛ Volatility spillover؛ Fluctuation؛ VECM and GARCH Family Models

مراجع

[1] Al-Yahyaee, K. H., Mensi, W., Sensoy, A., and Kang, S. H., Energy, precious metals, and GCC stock markets: Is there any risk spillover? Pacific-Basin Finance Journal, 2019, 56, P.45-70.

Doi: 10.1016/j.pacfin.2019.05.006

 

[2] Arago, V., Fernandez, M.A., Influence of structural changes in transmission of information between stock markets: A European Empirical Study, Journal of Multinational Financial Management, 2007, 17(1), P.112-124. Doi: 10.1016/j.mulfin.2006.05.002

 

[3] Hosseini, S.M., and Ebrahimi, S.B., Modeling and measuring the transmission of turbulence using multivariate GARCH models, Stock Exchange Quarterly, 2014, 21, P. 157-137.

 

[4] Bollerslev, T., Wooldridge, J.M., Quasi-maximumlikelihood estimation and inference in dynamicmodels with time-varying covariances. Econometric Reviews, 1992, 11, P.143–172. Doi: 10.1080/07474939208800229

 

[5] Bordbar, N., Heidari, E., The Effect of Global Oil Price Fluctuations on the Return on Energy Industries in Iran, Quarterly Journal of Economic Modeling Research, 2017, 27. Doi: 10.29252/jemr.7.27.177

 

[6] Borio, C., Lowe, P., Asset prices, financial and monetary stability: exploring the nexus, 2004, Available at http://www.bis.org/publ/work114.pdf.

 

[7] Botshekan, M. H., Sadeghi Shahedani, M., Salimi, M. J., and Mohseni, H., Spillover of Fluctuations on the Stock Exchange, Quarterly Journal of Economic Research and Policy, 2017, 25(84).

 

[8] Caldarelli, R., Elekdag, S.A., and Lall, S., Financial Stress, Downturns, and Recoveries, International Monetary Fund, Working Paper, 2009, WP/09/100.

 

[9] Chen, H., Liao, H., Tang, B.J., and Wei, Y.M., Impacts of OPEC's political risk on the international crude oil prices: An empirical analysis based on the SVAR models, Energy Economics, 2016, 57, P.42-49.

 Doi: 10.1016/j.eneco.2016.04.018

 

[10] Dasgupta, S., Roy, J., Understanding Technological and Input Price as Driver of Energy Demand in Manufacturing Industries in India, Energy Policy, 2015, 82, P.1-13. Doi: 10.1016/j.enpol.2015.03.024

 

[11] Diebold, F.X., Yilmaz, K., Better to give than to receive: predictive directional measurement of volatility spillovers, Int. J. Forecast, 2012, 28, P.57–66. Doi: 10.1016/j.ijforecast.2011.02.006

[12] David Brent, A., The Psychological Autopsy: Methodological Considerations for the Study of Adolescent Suicide, Journal of the American Academy of Child & Adolescent Psychiatry, 1974.

 Doi: 10.1111/j.1943-278x.1989.tb00365.x.

 

[13] Giuliodori, D., Rodriguez, A., Analysis of the stainless steel market in the EU, China and US using co-integration and VECM, Resources Policy, 2015, 44, P.12-24. Doi: 10.1016/j.resourpol.2014.11.006 

 

[14] Engle, R. F., Sheppard, K., Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH, Mimeo, UCSD, 2001.

 

[15] Engle, R.F., Granger, C.W.J., Co-integration and error-correction: Representation, estimation and testing, Econometrica, 1987, 55(2), P. 251-276. Doi: 10.2307/1913236

 

[16] Engle, R., Dynamic conditional correlation- a simple class of multivariate GARCH models, Journal of business and economic statistic, 2001, abstract.

 

[17] Ewing, B.T., Malik, F., Volatility transmission between gold and oil futures under structural breaks, International Review of Economics and Finance, 2013, 25(3), P.113–121. Doi: 10.1016/j.iref.2012.06.008

 

[18] Ewing, B.T., Malik, F., Volatility spillovers between oil prices and the stock market under structural breaks, Global Finance, 2015. Doi: 10.1016/j.gfj.2015.04.008

 

[19] Fasanya, I., Akinbowale, S., Modelling the return and volatility spillovers of crude oil and food prices in Nigeria, Energy, 2019, 169, P.186-205. Doi: 10.1016/j.energy.2018.12.011

 

[20] Fetri, M. H., Hoshidari, M., The effect of crude oil price fluctuations on the volatility of returns on the Tehran Stock Exchange, Iranian Journal of Energy Economics, 2016, 5(18).

 

[21] Gholami, N., Ghasemi, A., and Mohammadi, T., Designing a Network to Measure the Dynamics of the Relationships between Oil Volatility and Financial Markets, Quarterly Journal of Energy Economics Studies, 2016, 16(67), P.33-55.

 

[22] Heidari, H., Refah Kahriz, A., and Talebi, F., The effect of oil price fluctuations on the country risk index in OPEC member countries in different economic regimes, Quarterly Journal of Energy Economics Studies, 2018, 14(57).

 

[23] Hollo, D., Kremer, M., Lo, M., and Duca, M., CISS – A composite indicator of systemic stress in the financial system, European Central Bank working paper series no. 1426, 2012.

 

[24] Husain, S., Tiwari, A. K., Sohag, K., and Shahbaz, M., Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA, Resources Policy, 2019, 62, P.57-65.

Doi: 10.1016/j.resourpol.2019.03.011

 

[25] Illing, M., Liu, Y., Measuring financial stress in a developed country: an application to Canada, J. Financ. Stab. 2006, 2(4), P.243–265. Doi: 10.1016/j.jfs.2006.06.002

 

[26] Lamoureux, C. G., Lastrapes, W. D., Persistence in variance, structural change and the GARCH model, Journal of Business and Economic Statistics, 1990, 8, P.225–234. Doi: 10.2307/1391985

 

[27] Mamipour, S., Feli, A., Investigating the Spillover of Oil Price Volatility on the Returns of Selected Industries on the Tehran Stock Exchange. Monetary Economics, Financial Research (Former Knowledge and Development), 2017, 24(14).

 

[28] Nelson, W.R., Perli, R., Selected Indicators of Financial Stability, 2005, Available athttp://www.ecb.europa.eu/events/pdf/conferences/jcbrconf4/Perli.pdf.

 

[29] Nofaresti, M., The Unified and Cohesive Root in Econometrics, Rasa Publications, Second Edition, 2008.

 

[30] Lee, C.C., Lee, C.-C., and Ning, S.L., Dynamic Relationship of Oil Price Shocks and Country Risks, Energy Economics, 2017, 66(C), P. 571-581. Doi: 10.1016/j.eneco.2017.01.028

 

[31] Ono, S., Causality Relationship Among Oil Price, Stock Index and Exchange Rate: Evidence from Russia, Acta Slavica Iaponica, 2018, 35, P.87-107.

 

[32] Sefidbakht, E., Ranjbar, M. H., Study of Spillover of Fluctuations between Oil Price, Exchange Rate, Gold Price and Stock Market at Time intervals and Structural Failure Using GARCH Model (BEKK) and ICSS Algorithm, Journal of Securities’ Financial Engineering, 2017.

 

[33] Granger, C. W. J., Forecasting volatility in financial markets: A Review, Journal of Economic Literature, 2003, 41(5), P.478-539. Doi: 10.1257/002205103765762743

 

[34] Roy, J., Demand for Energy in Indian Manufacturing Industries, Dlhi Daya Publishing, 1991.

 

[35] Sehgal, S., Kapur, R., Relationship between oil price shocks and stock market performance: evidence for select global equity markets, Vision: The Journal of Business Perspective, 2012, 16(2), P.81-92.

Doi: 10.1177/097226291201600201

 

[36] Shahrazi, S., Elmi, Z., Abu Nouri, E., and Rasekhi, M. M., The Effect of Structural Failures of Fluctuations on Shock Transfer and Fluctuation Spillover between Iran's Gold and Stock Markets, Economic Modeling Quarterly, 2014, 8(26).

 

[37] Sharma, N., Khanna, K., Crude oil price velocity and stock market ripple a comparative study of BSE with NYSE & LSE, Indian Journal of Exclusive Management Research, 2012, 2(7), P.1-7. Doi:10.2139/ssrn.2122258

 

[38] Suri, Econometrics Volume (1), Fourth Edition. Farhangshenasi Publications, 2015.

 

[39] Suri, Econometrics Volume (2), Fourth Edition. Farhangshenasi Publications, 2015.

 

[40] Sujit, K. S., Kumar, B. R., Study on dynamic relationship among gold price, oil price, exchange rate and stock market returns, International Journal of Applied Business and Economic Research, 2011, 9(2), P.145-165.

 

[41] Yoon, S. M., Al Mamun, M., Uddin, G. S., and Kang, S. H., Network connectedness and net spillover between financial and commodity markets, The North American Journal of Economics and Finance, 2019, 48, P.801-818. Doi: 10.1016/j.najef.2018.08.012

 

[42] Luo, J., Wang, Sh., The asymmetric high-frequency volatility transmission across international stock markets, Finance Research Letters, Elsevier, 2019, 31(C), P.104-109. Doi: 10.1016/j.frl.2019.04.025

 

 

[43] Lee, C.C., Jhih-Hong, Z., The Impact of Price Shock on Stock Market Activity: Assymetric Effect with Quantile Regression, Journal of Mathematics and Computers in Simulation, 2011, 81, P.1910-1920.

Doi: 10.1016/j.matcom.2011.03.004

 

[44] Fallahi, F., Haghighat, J., Sanobar, N., and Jahangiri, Kh., Investigating the correlation between stock market, currency and coin market turmoil in Iran using the DCC- GARCH model, Economic Research Journal, 2014, Fourteenth Year, 3, P.147-123.

 

[45] Moghadam, M. R., and Sezavar, M. R., Investigating the Relationship between Macroeconomic Variables and Stock Price Index in the Stock Exchange, Journal of Business Studies, 2016, 75, February and March 2016.

 

[46] Fasanya, I., Akinbowale, S., Modelling the return and volatility spillovers of crude oil and food prices in Nigeria, Energy, Elsevier, 2019, 169(C), P.186-205. Doi: 10.1016/j.energy.2018.12.011

 

[47] Abbasian-Naghneh, S., Tehrani, R., Tamimi, M. The Effect of JCPOA on the Network Behavior Analysis of Tehran Stock Exchange Indexes. Advances in Mathematical Finance and Applications, 2021, 6(3), P. 465-477, Doi: 10.22034/amfa.2019.1873319.1258

 

[48] Zanjirdar, M. Overview of Portfolio Optimization Models. Advances in Mathematical Finance and Applications, 2020, 5(4), P. 419-435. Doi: 10.22034/amfa.2020.674941

[49] Zangenehmehr, P., Farajzadeh, A. On Solutions of Generalized Implicit Equilibrium Problems with Application in Game Theory, Advances in Mathematical Finance and Applications, 2022, 7(2), P. 391-404.

Doi: 10.22034/amfa.2021.1935453.1617

 

[50] Izadikhah, M. Financial Assessment of Banks and Financial Institutes in Stock Exchange by Means of an Enhanced Two stage DEA Model. Advances in Mathematical Finance and Applications, 2021, 6(2), P. 207-232. Doi: 10.22034/amfa.2020.1910507.1491

[51] Izadikhah, M. DEA Approaches for Financial Evaluation - A Literature Review, Advances in Mathematical Finance and Applications, 2022, 7(1), P. 1-36, Doi: 10.22034/amfa.2021.1942092.1639

 

[52] Salehi, A., Mohammadi, S., Afshari, M., Impact of Institutional Ownership and Board Independence on the Relationship Between Excess Free Cash Flow and Earnings Management. Advances in Mathematical Finance and Applications, 2017, 2(3), P. 91-105. Doi: 10.22034/amfa.2017.533104

[53] Parsa, B., Sarraf, F., Financial Statement Comparability and the Expected Crash Risk of Stock Prices. Advances in Mathematical Finance and Applications, 2018, 3(3), P. 77-93.

Doi: 10.22034/amfa.2018.544951

[54] Zanjirdar, M., Kasbi, P., Madahi, Z., Investigating the effect of adjusted DuPont ratio and its components
on investor & quot; s decisions in short and long term, Management Science Letters, 2014, 4(3), P.591-596.
Doi: 10.5267/j.msl.2014.1.003