Lahiani, Amine and Yousfi, Ouidad (2007): Modèls Garch à la mémoire longue: application aux taux de change tunisiens. Published in: Euro-Mediterranean Economics and Finance Review , Vol. 3, No. 4 (2008): pp. 106-122.
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Abstract
This paper deals with statistics�and econometrics�properties of fractionally integra- ted GARCH (FIGARCH). We compare these characteristics with those of traditional models. We insist on the GARCH exponential/IGARCH in�nite decrease of volatility impact. Then, we apply it on three Tunisian exchange rate series between 1994 and 2006. As Beine, Laurent and Lecourt (2002), the contributions of the FIGARCH model are extended by accounting for the observed kurtosis through a student-t based maximum likelihood estimation. This estimation improves the goodness of �t properties of this model and may lead to di¤erent interest parameters estimates.
Item Type: | MPRA Paper |
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Original Title: | Modèls Garch à la mémoire longue: application aux taux de change tunisiens |
English Title: | GARCH models : evidence from Tunisian Exchange market |
Language: | French |
Keywords: | Long memory, Volatility, persistence, exchange rate |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes F - International Economics > F3 - International Finance > F31 - Foreign Exchange |
Item ID: | 28702 |
Depositing User: | Ouidad YOUSFI |
Date Deposited: | 07 Feb 2011 14:31 |
Last Modified: | 26 Sep 2019 14:31 |
References: | Baillie, Bollerslev T.et Mikkelsen H.O., 1996, Fractionally integrated generalized autoregressive conditional heteroscedasticity, Journal of Econometrics 74, 3-30. Bollerslev, T., 1986, Generalized autoregressive conditional heteroscedasticity, Journal of Econometrics 31, 307-327. Bollerslev, T., Chou, R.Y., et Kroner, K.F., 1992, ARCH modelling in finance , Journal of Econometrics, 31, 307-327. Bollerslev, T., R.F. Engle and D.B. Nelson 1994, ARCH models, in R.F. Engle et D. McFadden, eds., Handbook of Econmetrics, Vol 4, Elevier Science B. V Amesterdam. Bollerslev, T. and H. O. Mikkelsen, 1996, Modeling and pricing long memory in stock market volatility, Journal of Econometrics 73, 151-184. Bougerol, N. et Picard, N.M., 1992, Stationarity of GARCH processes and of some nonnegative time series, Journal of Econometrics, 52, 115-127. Breidt, Crato et de Lima, 1998, The detection and estimation of long memory in stochastic volatility, Journal of Econometrics 83, 325-348. Caporin M., 2002, Long memory conditional heteroscedasticity and second order causality, université de Ca' Foscari Venise. Caporin, M, 2002, FIGARCH models: stationarity, estimation methods and the identification problem, Université de Ca' Foscari à Venise, n° 02.02. Chung, Ching-Fan, 2001, Estimating the fractionally integrated GARCH model, National Taiwan University discussion paper. Davidson, J., 2003, Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model, working paper. Ding, Z. and Granger, C.W.J., 1996, Modeling volatility persistence of speculative returns: A new approach. J. Econometrics 73, 185-215. Engle, R.F., 1982, Autoregressive conditional heteroscedasticity with estimates of the variance U.K. inflation. Engle, R.F., et Granger, C.W.J., 1985, Cointegration and Error Correction: Representation, Estimation and Testing. Econometrica. Engle, R.F., and T. Bollerslev, 1986, Modelling the persistence of conditional variances, Econometric reviews 5, 1-50. Giraitis, L., Koskoszka, P. et Leipus R., 2000, Stationary ARCH models : Dependence structure and central limit theorem, Econometric theory, 16,3-22. Granger, C.W.J., 1980, Long Memory Relationships and the Aggragation of Dynamics Models. Journal of Econometrics Granger et Joyeux, 1980, An Introduction to long memory time series models and fractional differencing, 1,15-29. Hosking, J.R.M., 1981, Fractional Differencing, Biometrica, n° 68 (1), 165-176. Kazakevicius, V., Leipus, R., 2001, Stationarity in the integrated ARCH models,Econometrics theory. Kazakevicius, V., 2002, A New Theorem on existence of invariant Distributions With Applications to ARCH processes, Applied probability Trust. Kazakevicius, V. et Leipus, R. 2002, On stationarity in the model, Econometrics theory. Lardic S. et Mignon V. , 1999, Prévision ARFIMA des taux de change: les modélisateurs doivent ils encore exhorter à la naîvité des prévisions?, Annales d'économie et de Statistique, 54, 47-68. Micosch, T. et Starica, C., 2000, Long range dependance effects and ARCH modelling, Preprint. Nelson, D.B., 1990, Stationarity and persistence in the GARCH( 1, 1) model , Econometric theory, 6, 318-334. Nelson, D.B, 1990 a, ARCH Models as Diffusion Approximation, Journal of Econometrics, 45, 7-38. Nelson, 1990 b, Stationarity and Persistence in The GARCH (1, 1) Model, Econometric Theory, 6, 318-334. Robinson et Zaffaroni, 2001, Pseudo_Maximum likelihood Estimation of Models, London School Of Economics et Banque d'Italie. Teyssière, G. 1996, Double long-memory financial time series, GREQAM. Zaffaroni P., 2002, Stationarity and memory of ARCH models, publication du STICERD, EM/2000/383. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/28702 |