Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH

Ouael EL JEBARI, Abdelati HAKMAOUI

Abstract


Abstract. We have tried in this article to detect, examine, and analyze the persistence in the conditional volatility of the major Moroccan stock market index called MASI, using a fractionally integrated EGARCH model that has the property of capturing long memory along with shocks to the conditional volatility. A GARCH (1,1) and IGARCH models were also estimated for comparative purposes using Akaike, Schwarz and log likelihood information criterion. We used daily returns of MASI index covering the period between 04/01/1993 and 03/02/2017. Our results confirm the presence of a strong persistence in the volatility of the Moroccan index which is inconsistent with the weak efficiency form of Fama’s efficient markets hypothesis. The findings of this study could be of particular use to investors and academics interested in the forecasting of daily volatility in the Moroccan context. This paper broadens previous long memory estimation research by applying a FIEGARCH specification enabling it, not only to account for persistence, but also, to measure the leverage effect. Moreover, we believe that, to the best of our knowledge, this paper is the first to model the volatility of the Moroccan stock market using a FIEGARCH approachng. 

Keywords. Volatility, Persistence, Long memory, FIEGARCH, MASI.

JEL. G11, G17, C53, C58.

Keywords


Volatility; Persistence; Long memory; FIEGARCH; MASI.

Full Text:


References


Antonakakis, N., & Darby, J. (2013). Forecasting volatility in developing countries’ nominal exchange returns. Applied Financial Economics, 23(21), 1675-1691. doi. 10.1080/09603107.2013.844323

Baillie, R.T., Bollerslev, T., & Mikkelsen, H.O. (1996). Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 74(1), 3–30. doi. 10.1016/S0304-4076(95)01749-6

Banerjee, A., & Sarkar, S. (2006). Modeling daily volatility of the Indian stock market using intra-day data. Calcutta: Indian Institute of Management. Working Paper No.WPSNO.588. [Retieved from].

Barkoulas, J.T., Baum, C.F., & Travlos, N. (2000). Long memory in the Greek stock market. Applied Financial Economics, 10(2), 177-184. doi. 10.1080/096031000331815

Beine, M., Laurent, S., & Lecourt, C. (2002). Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates. Applied Financial Economics, 12(8), 589-600. doi. 10.1080/09603100010014041

Bentes, S.R., Menezes, R., & Mendes, D.A. (2008), Long memory and volatility clustering: is the empirical evidence consistent across stock markets? Physica A, 387(15), 3826-3830. doi. 10.1016/j.physa.2008.01.046

Bollerslev, T., & Engle, R.F. (1993), Common persistence in conditional variances: definition and representations, Econometrica, 61(5), 167-186. doi. 10.2307/2951782

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. doi. 10.1016/0304-4076(86)90063-1

Brockwell, P.J., & Davis, R.A. (1987). Time Series: Theory and Methods, Springer-Verlag, New York.

Chambers, M.J. (1998). Long memory and aggregation in macroeconomic time series, International Economics Review, 39(4), 1053-1072. doi. 10.2307/2527352

Chou, R.Y. (1988), Volatility persistence and stock valuations: some empirical evidence using GARCH, Journal of Applied Econometrics, 3(4), 279-294. doi. 10.1002/jae.3950030404

Chow, K.V., Pan, M.-S. & Sakano, R. (1996). On the long-term or short-term dependence in stock prices: Evidence from international stock markets. Review of Quantitative Finance and Accounting, 6(2), 181-194. doi. 10.1007/BF00367503

Engle, R.F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric Reviews, 5(1), 1-50. doi. 10.1080/07474938608800095

Engle, R.F., & Gonzalez-Rivera, G. (1991). Semiparametric ARCH models, Journal of Business Economy and Statistics, 9(4), 345-360.

Engle, R.F., & Mustafa, C. (1992). Implied ARCH models from option prices, Journal of Econometrics, 52(1-2), 289-311. doi. 10.1016/0304-4076(92)90074-2

Engle, R.F., (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation. Econometrica, 50(4), 987-1008. doi. 10.2307/1912773

Fakhfekh, M., Jeribi, A., & Hachicha, N. (2015). Long memory properties on Tunisian sectorial stock market index volatilities: evidence from FIEGARCH model, International. Journal of Sustainable Economy, 7(4), 280-305. doi. 10.1504/IJSE.2015.072201

Fama, E.F. (1970). Efficient capital markets: A review of the theory and empirical work, Journal of Finance, 25(2), 383-417. doi. 10.2307/2325486

Gil-Alana, L.Z., Shittu, O.I., & Yaya, O.S. (2014). On the persistence and volatility in European, American and Asian stocks bull and bear markets, Journal of International Money Finance, 40, 149-162. doi. 10.1016/j.jimonfin.2012.12.002

Goudarzi, H. (2010). Modeling long memory in the Indian stock market using fractionally integrated egarch model, International Journal of Trade, Economics and Finance, 1(3), 231-237.

Granger, C.W.J., &. Joyeux, R. (1980). An introduction to long memory time series models and fractional differencing. Journal of Time Series Analysis, 1(1), 15-39. doi. 10.1111/j.1467-9892.1980.tb00297.x

Grau-Carles, P. (2005). Tests of long memory: A bootstrap approach. Computational Economics, 25(1-2), 103-113. doi. 10.1007/s10614-005-6277-6

Hoskin, J.R.M. (1981). Fractional differencing, Biometrika, 68(1), 165-176. doi. 10.1093/biomet/68.1.165

Huang, B.N., & Yang, C.W. (1999). An examination of long-term memory using the intraday stock returns. Clarion: Clarion University of Pennsylvania, Technical Report, No.99–03.

Hurst, H.E. (1951). Long-term story capacities of reservoirs, Trans. American Society of Civil Engineering. 116(1), 770–799.

Jin, H.J., & Frechette, D.L. (2004). Fractional integration in agricultural futures price volatilities. American Journal of Agricultural Economics, 86(2), 432-443. doi. 10.1111/j.0092-5853.2004.00589.x

Kang, S.H., Cheong, C., & Yoon, S.M. (2010), Long memory volatility in Chinese stock markets, Physica A, 389(7), 1425-1433. doi. 10.1016/j.physa.2009.12.004

Kasman, A., Kasman, S., & Torun, E. (2009). Dual long memory property in returns and volatility: evidence from the CEE countries’ stock markets, Emerging Markets Review, 10(2), 122-139. doi. 10.1016/j.ememar.2009.02.002

Mandelbrot, B.B., & Van Ness, J.W. (1968), Fractional Brownian motion, fractional noises and applications, SIAM Review, 10(4), 422-437. doi. 10.1137/1010093

Pagan, A.R., & Schwert, G.W. (1990), Alternative models for conditional stock volatility, Journal of Econometrics, 45(1-2), 267-290. doi. 10.1016/0304-4076(90)90101-X

Panas, E. (2001). Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange. Applied Financial Economics, 11(4), 395-402. doi. 10.1080/096031001300313956

Peters, E.E. (1996). Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility. New York: John Wiley & Sons. Inc.

Porteba, J., & Summers, L. (1987). The persistence of volatility and stock market fluctuations, American Economic Review, 76(5), 1142-1151.

Qiu, T.,Chen, G., Zhong, L.X., & Wu, X.R. (2012), Dynamics of bid-ask spread return and volatility of the Chinese stock market, Physica A, 391(8), 2656–2666. doi. 10.1016/j.physa.2011.12.048

Schwert, G.W., & Seguin, P.J. (1990), Heteroskedasticity in stock returns, Journal of Finance, 45(4), 1129-1155. doi. 10.1111/j.1540-6261.1990.tb02430.x




DOI: http://dx.doi.org/10.1453/ter.v4i4.1466

Refbacks

  • There are currently no refbacks.




.......................................................................................................................................................................................................................................................................................................................................

Turkish Economic Review - Turk. Econ. Rev. - TER - www.kspjournals.org

ISSN: 2149-0414

Editor: [email protected]   Secretarial: [email protected]   Istanbul - Turkey.

Copyright © KSP Library