PENGKLUSTERAN DATA TIME SERIES KEUANGAN DENGAN MODEL GARCH (1,1) PADA PASAR SAHAM INTERNASIONAL

Elfa Rafulta

Abstract


paper introduced a method clustering for financial data. By using the model Heteroskidastity Generalized autoregressive conditional (GARCH), will be estimated distance between the stock market using GARCH-based distance. The purpose of this method is mengkluster international stock markets with different amounts of data.

 

Keywords: GARCH, Cluster Analisis, Intenational Stock Markets

References


Caiado J, Crato N and Pena D. 2007. A GARCH-Based Method for Clustering of Financial Time Series: International Stock Markets Evidence.

Caiado J, Crato N and Pena D. 2007. Comparison of Time Series With Unequal Lengths, Manuscript. International Stock Markets Evidence.

Bollerslev T. 1986. Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31: 307-327.

Johnson RA and Wichern DW. 1992. Applied Multivariate Statistical Analysis. Englewood Clios, Prentice-Hall.

Bain LJ and Engelhardt M. 1992. Introduction To Probability and Mathematical Statistics 2nd Edition. Duxbury Press: California.

Engle R. 1982. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom in.ation. Journal of Econometrica, 50: 987-1008.

Brockwell PJ and Davis AR. 1991. Time Series: Theory and Methods, Springer Science. New York.

Wei WWS. 2006. Time Series Analysis Univariate and Multivariate Methods. New York.




DOI: http://dx.doi.org/10.31958/js.v4i1.61

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.