Robust Estimation in Nonlinear Modeling of Volatility Transmission in Stock Market

Document Type: Research Paper

Author

Department of Industrial Engineering, K.N.Toosi University of Technology, Tehran, Iran

Abstract

Volatility transmission means the connection between different markets in a way that volatility can be transmitted from one market to another. The volatility of oil price in global markets is one of the factors which influence the capital markets of the countries of which their economy is based on oil revenues. Most of these markets have long-run memory characteristic which should be considered in modeling and estimation. In this paper the long memory effect in BEKK model which is one of the main Multivariate models of volatility spillover is considered and the Boudt & Croux (2010) approache is used for stable estimation of the model. The data used in this paper are daily returns of stock prices and oil prices in time interval December 2006 to January 2012. The paper investigate the influence of world oil price index on Dubai and Tehran stock markets in the strategic region of Middle East and also the mutual transmission between the two main trading partner of Iran and Emirates.  The results indicate the volatility transmission from world oil market to Dubai and Tehran markets and also the transmission from Dubai market to Tehran market.

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Main Subjects


1. Boudt, K. and Croux, C. (2010). “Robust M- estimation of multivariate GARCH models”, Computational Statistics & Data Analysis, Vol. 54, No. 11, PP. 2459- 2469.
2. Hamilton, J. D. (1983). “Oil and Macro- Economy since world war II”, Journal of Political Economy, Vol.91, No. 2, PP. 228– 248.
3. Hamilton, J. D. (2003). “What is an oil shock?”, Journal of Econometrics, Vol.113, No. 2, PP. 363– 398.
4. Kilian, L. (2008b). “Exogenous oil supply shocks: How big are they and how much do they matter for the U.S. economy?”, Review ofEconomics and Statistics, Vol.90,  No. 2, PP. 216– 240.
5. Kilian, L. (2008a). “The economic effects of energy price shocks”, Journal of Economic Literature, Vol.46, No. 4, PP. 871– 1009.
6. Tansuchat, R., Chang, C. L. and McAleer, M. (2010). “Conditional correlation and volatility spillovers between crude oil and stock index returns”No.25, PP.116– 138.
 
7. Yu, J., and Hasan, M. K. (2008). “Global and regional integration of the Middle East and North African (MENA) stock markets”, The Quarterly Review of Economics and Finance, Vol.48, No. 3, PP. 482– 504.
8. Malik, F. and Hammoudeh, S. (2007). “Shock and volatility transmission in the oil, US and Gulf equity markets”, International Review of Economics and Finance, Vol. 16, No. 3, PP. 357- 368.
9. Aloui, C. and Jammazi, R. (2009). “The effects of crude oil shocks on stock market shifts behavior: A regime switching approach”, Energy Economics, Vol.31, No. 5, PP. 789- 799.
10. Arouri, M. and Nguyen, D. K. (2010). “Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade”, Energy Policy, Vol.38, No. 8, PP. 4528- 4539.
11. Wei, Y., Wang, Y. and Huang, D. (2010). “Forecasting crude oil market volatility: Further evidence using GARCH- class models”, Energy Economics, Vol. 32, No. 6, PP. 1477- 1484.
12. Mahmoudi, V., Mohammadi, S. and Chitsazan, H. (2010). “A study of long memory trend for international oil markets”, Economic Research Modelling, Vol. 1, No. 1, PP. 29- 48.
13. Mohammadi, S. and Chitsazan, H. (2011). “Analysing long run memory in Tehran stock exchange”, Journal of Economic Research, Vol. 45, No. 97, PP. 207- 226.
14. Mohammadi, H. and Sue, L. (2010). International evidence on crude oil price dynamics: Application of ARIMA-GARCH models, Energy Economics, Vol. 32, No. 5, PP. 1001-1008.
15. Filis, G., Degiannakis, S. and Floros, C. (2011). “Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries”, International Review of Financial Analysis, Vol.20, No. 3, PP. 152- 164.
16. Van Nguyen, T. (2013). “The stable relationship between crude oil price and petrol price: Evidence from multivariate GARCH model”, The Empirical Econometrics and Quantitative Economics Letters, Vol. 2, No. 2.
17. Ghorbel, A., Boujelbène, M. and Boujelbène, Y. (2012). “Volatility spillovers and dynamic conditional correlation between crude oil and stock market returns.” International Journal of Managerial and Financial Accounting (IJMFA), Vol. 4, No. 2, PP. 177- 194.
18. Girardi, G. and Tolga Ergün, A. (2013). “Systemic risk measurement: Multivariate GARCH estimation of CoVaR”, Journal of Banking & Finance, Vol. 37, No. 8, PP. 3169- 3180.
19. Nazlioglu, S., Erdem, C., & Soytas, U. (2013). Volatility spillover between oil and agricultural commodity markets. Energy Economics, Vol.36, PP.658-665. 20. Miralles- Marcelo, J. L. and Miralles-Quirós, M. D. M. (2013). “Multivariate GARCH models and risk minimizing portfolios: The importance of medium and small firms”, The Spanish Review of Financial Economics, Vol. 11, No. 1, PP. 29- 38.
21. Chang, C. L., McAleer, M. J. and Tansuchat, R. (2013). “Conditional correlations and volatility spillovers between crude oil and stock index returns”, North American Journal of Economics and Finance, Vol. 25, No.1, PP. 116–138.
22. Wang, Y., Wu, C. and Yang, L. (2016). “Forecasting crude oil market volatility: A Markov switching multifractal volatility approach”, International Journal of Forecasting, Vol. 32, No. 1, PP. 1- 9.
23. Chan, J. C. and Grant, A. L. (2016). “Modeling energy price dynamics: GARCH versus stochastic volatility”, Energy Economics, Vol. 54, No. 1, PP. 182- 189.
24. Serletis, A. and Xu, L. (2016). “Volatility and a century of energy markets dynamics”, Energy Economics, Vol. 55, No. 1, PP. 1- 9.
25. Palma, W, (2007). Long-memory time series, theory and methods, John Wiley & Sons, Inc, New Jersey.
26. Seyyed Hosseini S. M. and Ebrahimi S. B. (2013). “Comparing of volatility transmission model with consideration of long memory effect; Case study: Three selected industry index”, Journal of Financial Research, Vol. 15, No. 1, PP. 74- 51.
27. Seyyed Hosseini, S. M., Babakhani, M. and Ebrahimi, S. B. (2012). Introduction to volatility transmission models in stock market, Bours publication.
28. Jeantheau, T. (1998), “Strong consistency of estimators for multivariate ARCH models”, Econometric Theory, Vol. 14, No. 1, PP. 70- 86.
29. Muler, N. and Yohai, V. J. (2002). “Robust estimates for ARCH processes”, Journal of Time Series Analysis, Vol. 23, No. 3, PP. 341- 375.
30. Muler, N. and Yohai, V. J. (2008). “Robust estimates for GARCH models”, Journal of Statistical Planning and Inference, Vol. 138, No. 10, PP. 2918- 2940.
31. Pafka, S. and Matyas, L. (2001). “Multivariat diagonal FIGARCH: Specification, Estimation and application to modelling exchange rate volatility”, Available at http://ideas.repec.org. PP. 5- 7.