PERBANDINGAN MODEL GLOSTEN, JAGANNATHAN AND RUNKLE – GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GJR-GARCH) DAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) DALAM ANALISIS RISIKO SAHAM SYARIAH

DINUL DARMA ATMAJA, NIM. 13610004 (2017) PERBANDINGAN MODEL GLOSTEN, JAGANNATHAN AND RUNKLE – GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GJR-GARCH) DAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) DALAM ANALISIS RISIKO SAHAM SYARIAH. Skripsi thesis, UIN Sunan Kalijaga Yogyakarta.

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	Text (PERBANDINGAN MODEL GLOSTEN, JAGANNATHAN AND RUNKLE – GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GJR-GARCH) DAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) DALAM ANALISIS RISIKO SAHAM SYARIAH) 13610004_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (13MB)

Abstract

The modeling of the return index of the Jakarta Islamic Index (JII) using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is not able to accommodate the asymmetrical response to shocks. This asymmetric response is known as "leverage effect". Therefore, it is necessary to use modeling technique from conditional heteroscedasticity class that is able to accommodate the asymmetric effect of shocks, so that in this study aims to find out the magnitude of risk on JII index return by comparing Value at Risk (VaR) Glosten, Jagannathan and Runkle – Generalized Autoregressive Conditional Heteroscedasticity (GJR-GARCH) and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). The results of a large risk test between the GJR-GARCH and EGARCH models on the JII index returns during the June 2014 – June 2017 period, monitored on daily frequencies, show similar results in a large predicted risk model that can be predicted only one day ahead but different for large the maximum estimated losses for each model within the next day. In the GJR-GARCH model obtained the maximum value of estimated losses in the next day of Rp. 295,244 with investment capital of Rp. 10.000.000, while in EGARCH model obtained the maximum value of estimated losses in one day ahead of Rp. 439,979 with investment capital of Rp. 10,000,000. From these two models by comparing the greatest risk obtained it can be seen that the GJR-GARCH model has a smaller risk than the EGARCH model. So it can be concluded that in this study the best model to analyze the risk of sharia stock is GJR-GARCH model.

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