Modelling Malaysia stock markets using GARCH, EGARCH and copula models

Journal of Optimization in Industrial Engineering

دوره 15، شماره 2 - شماره پیاپی 33، آذر 2022، صفحه 295-303   

نوع مقاله: Original Manuscript

شناسه دیجیتال (DOI): 10.22094/joie.2022.1961703.1967

نویسندگان

Nurul Hanis Aminuddin Jafry^{* 1}؛ Ruzanna Ab Razak²؛ Noriszura Ismail¹

¹School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

²Quantitative Methods Unit, Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia

چکیده

Copula is a favored method used to measure dependency for financial data due to its flexibility. Yet, studies about dependence structure between bivariate data especially by using time-varying copula approach is very limited. Hence, this paper will examine the dependency between KLCI-FBMHS pair by considering static and time-varying copula. Traditionally, ARCH model is used to measure the volatility. However, it failed to capture stylized facts that usually exist in financial data such as the volatility clustering and leverage effect. Thus, the study also investigates the effect of different marginal models (GARCH and EGARCH) towards dependence structure and parameter estimations. Generally, the findings reveal that KCLI-FBMHS pair have strong dependency. In addition, this study highlight that ARMA(1,0)-GARCH(1,1) and ARMA(1,0)-EGARCH(1,1) with student t distribution are well-fitted to both (KLCI and FBMHS) series, the KLCI-FBMHS pair have similar dependence structure for both static and dynamic copula models.

کلیدواژه‌ها

Time-varying Copula؛ GARCH؛ EGARCH؛ KLCI-FBMHS

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