Buriev, Abdul Aziz and Masih, Mansur (2015): Impact of Arab uprising on Portfolio diversification benefits at different investment horizons for the Turkish investors in relation to the regional stock markets: Multivariate GARCH-DCC and Wavelet coherence approaches.
Preview |
PDF
MPRA_paper_65233.pdf Download (960kB) | Preview |
Abstract
The current political changes in the Arab countries have raised concerns about the behaviour of stock markets in the region. It brings an expectation of distortions in the behaviour of the regional financial markets. This study aims at analysing the dynamic relationship between Middle Eastern and North African equity markets exposed to the Arab Spring, namely Turkey, Egypt, Oman, and Lebanon, using Multivariate GARCH-DCC and Wavelet Coherence techniques on weekly data spanning from 2005 to 2015. We employ Multivariate GARCH-DCC to find out the time-varying volatilities and correlations between the markets, and Wavelet Coherence based on Continuous Wavelet Transform followed by the multiscale variance, covariance, and correlations based on Maximal Overlap Discrete Wavelet Transform are used for multi-resolution analysis to see the pattern of interactions between the stock markets across the time-scales: low, medium, and high. The findings tend to suggest that the correlations between the stock markets are quite low all over the period: on average, about 4% until the Global Financial Crisis and 10% afterwards. In general, the volatilities are relatively stable, except for the global financial turmoil period. In particular, equity markets of Lebanon and Egypt display a slightly higher volatility during the Arab Spring. It means that the Turkish investors who have allocated their investments in major trading partners like Egypt may not experience great diversification benefits for almost all investment horizons related to higher trade intensity but moderate benefits arise for Lebanon up to the investment horizons of 32-64 days and longer. However, portfolio diversification benefits are greater if Turkish investors invest in the Oman stock index except during long investment horizons. As for the long run, stock holding periods exceeding 32-64 days have minimal benefits for portfolio diversification. As an implication, Turkish investors should carry out the reassessment of their stock exposures and investment horizons more frequently.
Item Type: | MPRA Paper |
---|---|
Original Title: | Impact of Arab uprising on Portfolio diversification benefits at different investment horizons for the Turkish investors in relation to the regional stock markets: Multivariate GARCH-DCC and Wavelet coherence approaches |
English Title: | Impact of Arab uprising on Portfolio diversification benefits at different investment horizons for the Turkish investors in relation to the regional stock markets: Multivariate GARCH-DCC and Wavelet coherence approaches |
Language: | English |
Keywords: | Arab uprisings, portfolio diversification, MGARCH-DCC, Wavelet Coherence |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions |
Item ID: | 65233 |
Depositing User: | Professor Mansur Masih |
Date Deposited: | 24 Jun 2015 07:23 |
Last Modified: | 06 Oct 2019 22:07 |
References: | Abou-Zaid, A. S. (2011). Volatility Spillover Effects in Emerging MENA Stock Markets. RAE, 7(1-2). Ali, S., Butt, B. Z., & Rehman, K. (2011). Comovement between emerging and developed stock markets: an investigation through cointegration analysis. World Applied Sciences Journal, 12(4), 395-403. Ali, S., Butt, B. Z., & Rehman, K. (2011). Comovement between emerging and developed stock markets: an investigation through cointegration analysis. World Applied Sciences Journal, 12(4), 395-403. Aloui, C., & Hkiri, B. (2014). Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis. Economic Modelling, 36, 421-431. Aloui, C., & Hkiri, B. (2014). Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis. Economic Modelling, 36, 421-431. Assidenou, K. E. (2011). Cointegration of major stock market indices during the 2008 global financial distress. International Journal of Economics and Finance, 3(2), 212. Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: a multivariate generalized ARCH model. The Review of Economics and Statistics, 498-505. Celık, S. (2012). The more contagion effect on emerging markets: The evidence of DCCGARCH model. Economic Modelling, 29(5), 1946-1959. Celık, S. (2012). The more contagion effect on emerging markets: The evidence of DCCGARCH model. Economic Modelling, 29(5), 1946-1959. Chau, F., Deesomsak, R., & Wang, J. (2014). Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries. Journal of International Financial Markets, Institutions and Money, 28, 1-19. Dewandaru, G., Masih, R., & Masih, A. M. M. (2015). Why is no financial crisis a dress rehearsal for the next? Exploring contagious heterogeneities across major Asian stock markets. Physica A: Statistical Mechanics and its Applications, 419, 241-259. Dewandaru, G., Rizvi, S. A. R., Masih, R., Masih, M., & Alhabshi, S. O. (2014). Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis. Economic Systems, 38(4), 553-571. Gençay, R., Selçuk, F., & Whitcher, B. (2001). Differentiating intraday seasonalities through wavelet multi-scaling. Physica A: Statistical Mechanics and its Applications, 289(3), 543556. Kabir,SH, Masih, AMM, & Bacha,O.I, , ‘Are Islamic equities Immune to Global Financial Turmoil? An Investigation of the Time Varying Correlation and Volatility of Islamic Equity Returns’, Australian Journal of Basic and Applied Sciences, Vol. 7, No. 7, 686-701. Karim,BA & Majid,MS 2010, ‘Does trade matter for stock market integration’ ,Studies in Economics and Finance, Vol. 27 No.1 2010, 47-66. Khan, T. A. (2011). Cointegration of international stock markets: An investigation of diversification opportunities. Undergraduate Economic Review, 8(1), 7. Lanza, A., Manera, M., & McAleer, M. (2006). Modeling dynamic conditional correlations in WTI oil forward and futures returns. Finance Research Letters, 3(2), 114-132. Lebo, M. J., & Box‐Steffensmeier, J. M. (2008). Dynamic conditional correlations in political science. American Journal of Political Science, 52(3), 688-704. Madaleno, M., & Pinho, C. (2010). Relationship of the multiscale variability on world indices. Revista De EconomiaFinanciera, 20, 69-92. Najeeb, S. F., Bacha, O., & Masih, M. (2015). Does Heterogeneity in Investment Horizons Affect Portfolio Diversification? Some Insights Using M-GARCH-DCC and Wavelet Correlation Analysis. Emerging Markets Finance and Trade, (ahead-of-print), 1-21. Pesaran, M. H., & Timmermann, A. (1995). Predictability of stock returns: Robustness and economic significance. The Journal of Finance, 50(4), 1201-1228. Saiti, B., Bacha, O. I., & Masih, M. (2014). The diversification benefits from Islamic investment during the financial turmoil: The case for the US-based equity investors. Borsa Istanbul Review, 14(4), 196-211. Tse, Y. K., & Tsui, A. K. C. (2002). A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business & Economic Statistics, 20(3), 351-362. You, L., & Daigler, R. T. (2010). Is international diversification really beneficial?. Journal of Banking & Finance, 34(1), 163-173. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/65233 |