| dc.contributor |
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| dc.contributor |
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| dc.creator |
Mufti, Wahyuni Fatma |
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| dc.creator |
Darwis, Sutawanir |
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| dc.creator |
Hajarisman, Nusar |
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| dc.date |
2016-02-18 |
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| dc.identifier |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/2624 |
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| dc.description |
Time commercial enterprises appear and provide more effective tools and devices for the future of the enterprises to solve dilemma of profit and create new profit growth. Value at Risk (VaR) model is used to solve the problems of time commercial enterprises. VaR model is a model used to measure the trade risk such as market risk, credit risk and so forth. The risk of VaR model refers to certain level of trust, in the period of the biggest loss probability. Data modelling of time series is done by variant assumption of constant error (homoscedasticity). In fact, many time series data have error variant that is inconstant (heteroscedasticity), especially for time series data in finances. It causes the modelling with the assumption of homoscedasticity is not used. Engle (1982) develops a model whose lines and kinds of time series data are modelled simultaneously. The model is know as Autoregressive Conditional Heteroscedasticity (ARCH) model. ARCH model is applied in share close price of Bank Mandiri to determine Value at Risk (VaR). |
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| dc.description |
Perusahaan perdagangan berjangka muncul dan menyediakan sarana yang lebih efektif bagi masa depan perusahaan untuk memecahkan dilema keuntungan dan menciptakan pertumbuhan laba baru. Untuk mengatasi masalah perusahaan perdagangan berjangka digunakan model Value at Risk (VaR). Model VaR adalah model yang digunakan untuk mengukur risiko perdagangan seperti risiko pasar, risiko kredit dll. Model VaR risikonya mengacu pada tingkat kepercayaan tertentu, pada periode terhadap kemungkinan kerugian terbesar. Pemodelan data deret waktu dilakukan dengan asumsi varian galat konstan (homoskedastisitas) yaitu . Kenyataannya, banyak data deret waktu yang mempunyai varian galat yang tidak konstan (heteroskedastisitas), khususnya untuk data deret waktu dibidang keuangan. Hal ini menyebabkan pemodelan dengan asumsi homoskedastisitas tidak digunakan. Engle (1982) mengembangkan model dimana rata dan ragam suatu data deret waktu dimodelkan secara simultan. Model tersebut dikenal dengan model Autoregressive Conditional Heteroscedasticity (ARCH). Model ARCH diterapkan pada harga close saham Bank Mandiri untuk menentukan Value at Risk (VaR). |
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| dc.format |
application/pdf |
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| dc.language |
ind |
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| dc.publisher |
Universitas islam Bandung |
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| dc.relation |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/2624/pdf |
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| dc.source |
Prosiding Statistika; Vol 2, No 1, Prosiding Statistika (Februari, 2016); 63-70 |
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| dc.source |
Prosiding Statistika; Vol 2, No 1, Prosiding Statistika (Februari, 2016); 63-70 |
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| dc.source |
2460-6456 |
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| dc.subject |
Proceedings of Statistics |
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| dc.subject |
Value at Risk (VaR), Heteroscedasticity, ARCH, Share. |
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| dc.subject |
Statistika |
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| dc.subject |
Value at Risk (VaR), Heteroskedastisitas, ARCH, Saham |
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| dc.title |
Calculation of Value at Risk (VaR) based on Autoregressive Conditional Heteroscedasticity (ARCH) model. |
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| dc.title |
Perhitungan Value at Risk (VaR) Berdasarkan Model Autoregressive Conditional Heteroscedasticity (ARCH) |
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| dc.type |
info:eu-repo/semantics/article |
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| dc.type |
info:eu-repo/semantics/publishedVersion |
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| dc.type |
Peer-reviewed Article |
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| dc.type |
Quantitative |
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| dc.type |
Kuantitatif |
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