ESTIMASI VALUE AT RISK (VAR) PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE COPULA-GARCH (STUDI KASUS SAHAM ICBP DAN UNVR PERIODE 1 MEI 2014 – 30 APRIL 2018)

YAYUK TRI LESTARI, NIM. 14610031 (2018) ESTIMASI VALUE AT RISK (VAR) PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE COPULA-GARCH (STUDI KASUS SAHAM ICBP DAN UNVR PERIODE 1 MEI 2014 – 30 APRIL 2018). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

Preview	Text (ESTIMASI VALUE AT RISK (VAR) PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE COPULA-GARCH (STUDI KASUS SAHAM ICBP DAN UNVR PERIODE 1 MEI 2014 – 30 APRIL 2018)) 14610031_BAB-I_BAB-VI_DAFTAR-PUSTAKA.pdf - Published Version Download (11MB) | Preview
	Text (ESTIMASI VALUE AT RISK (VAR) PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE COPULA-GARCH (STUDI KASUS SAHAM ICBP DAN UNVR PERIODE 1 MEI 2014 – 30 APRIL 2018)) 14610031_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (9MB)

Abstract

Investment in the financial sectorbis currently being done by investors but many investors do not know the result of their investements, the investement can bring profit or loss. One way to reduce the risk receives by investors is by investing in a portfolio. The portfolio itself is a collection or several assets or securities that are invested by investors to reduce the risk received. Risk can be managed by estimating using a value at risk measure. This study uses the Copula- GARCH method to calculate the risk obtained. GARCH (Generalized Autoregressive Conditional Heterocedasticity) is an autoregressive time series approach model. GARCH has the advantages that the residuals variance that is formed tends to be constant or these is no heterocedasticity effect. However, time series models generally cannot fulfill the assumption of normality. Copula is a function that can combine or install a multivariate distribution function with a dimensional marginal distribution function. Copula itself has the advanteages of not requiring the assumption of normality. In this study, copula used copula Clayton, Copula Frank, and copula Gumbel. So if there is a normality assumption, if there is no GARCH modeling, then it will be followed by copula odelling to calculate the risk of using VaR. This study estimates VaR by using Copula-GARCH in two stocks with the highest correlation value of 0.325, namely the iCBP and UNVR stock daily return for 1 May 2014 until 30 April 2018. In VaR calculation using the Monte Carlo simulation it will be known that the greater the return simulation performed the more constant the risk received by the Archamedian copula. The simulation return who used 100, 500, 1.000 and 10.000 with the risk of obtained copula Clayton are 12.68%, 12.12%, 11.68% dan 11.68%.

Share this knowledge with your friends :

Actions (login required)

View Item