Severity: Warning
Message: fopen(/var/cpanel/php/sessions/ea-php73/PHPSESSIDa821272a46462510a961e6f7e9b0b87e): failed to open stream: No space left on device
Filename: drivers/Session_files_driver.php
Line Number: 157
Backtrace:
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 173
Function: _ci_load_library
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 190
Function: library
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 153
Function: libraries
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 65
Function: initialize
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Base.php
Line: 55
Function: __construct
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Base.php
Line: 60
Function: __construct
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Controller.php
Line: 4
Function: require
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Modules.php
Line: 134
Function: include_once
File: /home1/ditlitluaracadst/public_html/acadstaff/application/core/MY_Controller.php
Line: 5
Function: spl_autoload_call
File: /home1/ditlitluaracadst/public_html/acadstaff/index.php
Line: 318
Function: require_once
Severity: Warning
Message: session_start(): Failed to read session data: user (path: /var/cpanel/php/sessions/ea-php73)
Filename: Session/Session.php
Line Number: 141
Backtrace:
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 173
Function: _ci_load_library
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 190
Function: library
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 153
Function: libraries
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Loader.php
Line: 65
Function: initialize
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Base.php
Line: 55
Function: __construct
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Base.php
Line: 60
Function: __construct
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Controller.php
Line: 4
Function: require
File: /home1/ditlitluaracadst/public_html/acadstaff/application/third_party/MX/Modules.php
Line: 134
Function: include_once
File: /home1/ditlitluaracadst/public_html/acadstaff/application/core/MY_Controller.php
Line: 5
Function: spl_autoload_call
File: /home1/ditlitluaracadst/public_html/acadstaff/index.php
Line: 318
Function: require_once
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) Prof. Dr. Drs. Gunardi, M.Si. (3) Prof. Dr. Abdurakhman, S.Si., M.Si. (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
|
No | Title | 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
|
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
|
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
|
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
|
View |