Affandi, Luqman (2018) Estimasi Parameter-Parameter Yield Surat Utang Negara Indonesia Menggunakan Metode Ensemble Kalman Filter. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Yield to maturity merupakan keuntungan yang diperoleh oleh seorang investor dalam membeli obligasi hingga jatuh tempo tiba. Model Diebold dan Li merupakan modi�kasi dari Model Nelson Siegel dimana model Diebold dan Li mempresentasikan yield to maturity dari obligasi-obligasi dengan waktu jatuh tempo yang beragam. Parameter ��β_1t, ��β_2t, ��β_3t, λ_t pada model Diebold dan Li sangat berpengaruh dalam menentukan kurva yield, Oleh karena itu, dibutuhkan suatu metode estimasi agar nantinya kurva yield sesuai dengan kondisi riil. Metode yang akan digunakan untuk estimasi parameter adalah metode Ensemble Kalman Filter. Hasil yang diperoleh untuk penyesuaian estimasi dari data Yield diambil dari Surat Utang Negara Indonesia tahun 2010 sampai 2018.
================================================================================Yield to maturity is pro�t obtained by an investor in purchasing bond until maturity comes. Diebold and li model is a modi�cation from Nelson Siegel model where it presents yield to maturity from bonds with variative maturity time. Parameters �β_1t, ��β_2t, ��β_3t, λ_t in Diebold and Li model are very influential in determining Yield Curve. Therefore it is needed an estimation method such that Yield Curve is suitable with real condition. The method that will be used for estimation of parameters is Ensemble Kalman Filter method. The result obtained for estimation adjustment from yield dates is taken from Indonesia Government bond in the span of 2010 to 2018.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMa 518.1 Aff e |
| Uncontrolled Keywords: | Kurva Yield, Model Diebold dan Li dan Ensemble Kalman Filter |
| Subjects: | Q Science > QA Mathematics > QA402.3 Kalman filtering. |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | Affandi Luqman |
| Date Deposited: | 04 Nov 2020 07:34 |
| Last Modified: | 04 Nov 2020 07:34 |
| URI: | http://repository.its.ac.id/id/eprint/59207 |
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