PEMODELAN VOLATILITAS UNTUK PENGHITUNGAN VALUE AT RISK (VaR) MENGGUNAKAN FEED FORWARD NEURAL NETWORK DAN ALGORITMA GENETIKA
High fluctuations in stock returns is one problem that is considered by the investors. Therefore we need a model that is able to predict accurately the volatility of stock returns. One model that can be used is a model Generalized Autoregressive Conditional Heteroskedasticity (GARCH). This model can...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Diponegoro
2014-12-01
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| Series: | Media Statistika |
| Online Access: | https://ejournal.undip.ac.id/index.php/media_statistika/article/view/8489 |