Iswandi, Iswandi (2017) Perbandingan Model Volatilitas dengan Indeks Saham di Asean = Comparation Modeling of Volatility in Asean Stock Index. Bachelor thesis, Universitas Pelita Harapan.
Full text not available from this repository.Abstract
Pada Tugas Akhir ini akan dibahas mengenai karakteristik dari volatilitas di negara-negara ASEAN. Model volatilitas yang digunakan adalah Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH),
Fractionally Integrated Generalized Autoregressive Conditional Heteroscedasticity (FIGARCH), Glosten Jaganathan Runkle Generalized Autoregressive Conditional Heteroscedasticity (GJR-GARCH), Multifractal Model of Asset return (MMAR). Dari hasil parameter dapat terlihat bahwa return dari negara-negara tersebut mempunyai karakteristik yang disebut long-term memory. Kemudian hasil parameter dari model volatilitas tersebut disimulasikan sehingga menghasilkan data yang baru. Data hasil simulasi tersebut dibandingkan dengan data yang asli dengan melihat scaling function. Data yang digunakan indeks saham dari negara
Filipina, Indonesia, Malaysia, Singapura, dan Thailand dari 1 Januari 2002 sampai 31 Januari 2016. Hasilnya adalah indeks saham di ASEAN memiliki long-term memory. Model yang cocok secara umum digunakan adalah MMAR karena model ini menggunakan Hurst Exponent sebagai parameter dari long-term memory.
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This thesis discusses about the characteristic of the volatility ASEAN stock index. Volatility model that used in this thesis are Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential Generalized
Autoregressive Conditional Heteroscedasticity (EGARCH), Fractionally Integrated Generalized Autoregressive Conditional Heteroscedasticity (FIGARCH), Glosten Jaganathan Runkle Generalized Autoregressive Conditional Heteroscedasticity (GJR-GARCH), Multifractal Model of Asset return (MMAR). The result of the parameter can be see that the return of the countries have a characteristic that is being called long-term memory. The simulated data is being
compared with the original data by scaling function. The data that used in this thesis are Filipina, Indonesia, Malaysia, Singapore, and Thailand stock index from 1 January 2002 until 31 January 2016. The result are in ASEAN stock index, it have long-term memory. The model that fitted to the data is MMAR because this model use Hurst Exponent as parameter of long-term memory.
Item Type: | Thesis (Bachelor) |
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Creators: | Creators NIM Email ORCID Iswandi, Iswandi NIM1305000510 UNSPECIFIED UNSPECIFIED |
Contributors: | Contribution Contributors NIDN/NIDK Email Thesis advisor Saputra, Kie Van Ivanky NIDN0401038203 kie.saputra@uph.edu Thesis advisor Kim, Sung Suk NIDN8963400020 sungsuk.kim@uph.edu |
Uncontrolled Keywords: | generalized autoregressive conditional heteroscedasticity (GARCH); exponential generalized autoregressive conditional heteroscedasticity (EGARCH); fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH); glosten jaganathan runkle generalized autoregressive conditional heteroscedasticity (GJR-GARCH); multifractal model of asset return (MMAR); scaling function; hurst exponent; indeks saham ASEAN; volatilitas. |
Subjects: | Q Science > QA Mathematics |
Divisions: | University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics |
Depositing User: | Stefanus Tanjung |
Date Deposited: | 01 Nov 2023 03:30 |
Last Modified: | 01 Nov 2023 03:30 |
URI: | http://repository.uph.edu/id/eprint/58585 |