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Title : CALIBRATING THE NELSON- SIEGEL MODEL CLASSES AND THEIR ESTIMATION USING HYBRID-GENETIC ALGORITHM APPROACH: CASE STUDY OF INDONESIAN GOVERNMENT BONDS
Author :

MUSLIM (1) Prof. Dr.rer.nat. Dedi Rosadi, S.Si., M.Sc. (2) Dr. Drs. Gunardi, M.Si. (3) Dr. Abdurakhman (4)
Date : 31 2019
Keyword : ield Curve, Nelson-Siegel Model, Hybrid Method, Genetic Algorithm, Nonlinear Least Square, and Constrained Optimization ield Curve, Nelson-Siegel Model, Hybrid Method, Genetic Algorithm, Nonlinear Least Square, and Constrained Optimization
Abstract : In this paper, we consider the problem of modelling the yield c urve using Nelson-Siegel model classes. Nelson-Siegel model classes discussed here are NS model, BL mod el, NSS model, RF model, and our proposed NSSE models. NSSE model is a model which extends the s tandard NS model as Nelson-Siegel model class by adding some linear and non-linear parameters in which form the fourth hump of the model class. The purpose of adding the hump is to accommodate the pos sibility of having the following cases: the first, the condition when the sho rt term and the medium term yi elds are higher than the long term yield. The second, the condition when the upper-value short term yields ar e higher than both the short term yields on average and the long term yields. The third, the case when the upper-value medium term yields are higher than both the medium term yields on average and the long term y ields. These considered cases make the yield curve more likely to have minimum locals and therefore, t he Nelson-Siegel model classes become more difficult to be estimated. To overcome this problem, in th is paper we estimate the model using the hybrid-genetic algorithm approach and compare it with the stand ard estimation based on NLS method. We provide an empirical study using Indonesian Government-Bond Yie ld Curve (IGYC) data, and found that the best model for IGYC is 6-factors model.
Group of Knowledge : Statistik
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 6-2019-Calibrating the nelson-siegel model classes and their estimation using hybrid-genetic algorithm approach - Case study of indonesian government bonds(1).pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
2 2019:2020-2-JIB40-Calibrating the nelson-siegel model classes and their estimation using hybrid-genetic algorithm approach - Case study of indonesian government bonds (1).pdf
Document Type : [PAK] Halaman Editorial
[PAK] Halaman Editorial View
3 2019:2020-2-JIB40-Calibrating the nelson-siegel model classes and their estimation using hybrid-genetic algorithm approach - Case study of indonesian government bonds (1).pdf
Document Type : [PAK] Halaman Cover
[PAK] Halaman Cover View
4 2019:2020-2-JIB40-Calibrating the nelson-siegel model classes and their estimation using hybrid-genetic algorithm approach - Case study of indonesian government bonds (1).pdf
Document Type : [PAK] Daftar Isi
[PAK] Daftar Isi View