The Economics and Finance Letters

Published by: Conscientia Beam
Online ISSN: 2312-430X
Print ISSN: 2312-6310
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No. 2

Estimating Value at Risk for Sukuk Market Using Generalized Auto Regressive Conditional Heteroskedasticity Models

Pages: 8-23
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Estimating Value at Risk for Sukuk Market Using Generalized Auto Regressive Conditional Heteroskedasticity Models

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DOI: 10.18488/journal.29/2015.2.2/29.2.8.23

Citation: 2

Pantea Hafezian , Hussin Salamon , Mahendran Shitan

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Pantea Hafezian , Hussin Salamon , Mahendran Shitan (2015). Estimating Value at Risk for Sukuk Market Using Generalized Auto Regressive Conditional Heteroskedasticity Models. The Economics and Finance Letters, 2(2): 8-23. DOI: 10.18488/journal.29/2015.2.2/29.2.8.23
In this paper, we compare the forecasting ability of different GARCH models to estimate value at risk in sukuk market.  A wide extensive list of both symmetric and asymmetric GARCH models (including GARCH, EGARCH, GJR-GARCH, IGARCH and Asymmetric power GARCH) were considered in modeling  the volatility in the sukuk market. All VaR estimations are carried out by “rugarch” package in “R” software. The performance of these models is compared by both in-sample and out-of-sample analysis.  We found that the performance of asymmetric models in estimating value at risk are superior in both in-sample and out-of-sample evaluation. We also found that in most cases the student-t distribution is more preferable than normal or generalized error distribution (GED).
Contribution/ Originality
This study is one of very few studies which have investigated the behavior of sukuk data in secondary market and describes characteristics of its statistical distribution function. Another contribution is comparing the estimation ability of various GARCH models in order to find superior model to estimate VAR in sukuk market.