Article Per Year (5 Year)
p-Index From 2019 - 2024
1.203
P-Index
This Author published in this journals
All Journal EKSAKTA: Journal of Sciences and Data Analysis Indonesian Journal of Statistics and Its Applications Variance : Journal of Statistics and Its Applications REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat
Fajar Indrayatna
Actuarial Science, Department Of Statistics, Universitas Padjadjaran, Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Indonesian Journal of Statistics and Its Applications

 1 
Estimation of Value at Risk by Using GJR-GARCH Copula Based on Block Maxima Hasna Afifah Rusyda; Fajar Indrayatna; Lienda Noviyanti
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p405-414

Abstract

This paper will discuss the risk estimation of a portfolio based on value at risk (VaR) using a copula-based asymmetric Glosten – Jagannathan – Runkle - Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH). There is non-linear correlation for dependent model structure among the variables that lead to the inaccurate VaR estimation so that we use copula functions to model the joint probability of large market movements. Data is GEV distributed. Therefore, we use Block Maxima consisting of fitting an extreme value distribution as a tail distribution to count VaR. The results show VaR can estimate the risk of portfolio return reasonably because the model has captured the data properties. Data volatility can be accommodated by GJR-GARCH, Copula can capture dependence between stocks, and Block maxima can accommodate extreme tail behavior of the data.
Estimation of Value at Risk by Using GJR-GARCH Copula Based on Block Maxima Hasna Afifah Rusyda; Fajar Indrayatna; Lienda Noviyanti
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p405-414

Abstract

This paper will discuss the risk estimation of a portfolio based on value at risk (VaR) using a copula-based asymmetric Glosten – Jagannathan – Runkle - Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH). There is non-linear correlation for dependent model structure among the variables that lead to the inaccurate VaR estimation so that we use copula functions to model the joint probability of large market movements. Data is GEV distributed. Therefore, we use Block Maxima consisting of fitting an extreme value distribution as a tail distribution to count VaR. The results show VaR can estimate the risk of portfolio return reasonably because the model has captured the data properties. Data volatility can be accommodated by GJR-GARCH, Copula can capture dependence between stocks, and Block maxima can accommodate extreme tail behavior of the data.
Co-Authors Achmad Zabar Soleh Achmad Zanbar Soleh Adri Arisena Anindya Apriliyanti Pravitasari Anna Chadidjah Gumgum Darmawan Hasna Afifah Rusyda Intan Nurma Yulita Lienda Noviyanti Mulya Nurmansyah Ardisasmita Mulya Nurmasnsyah Ardisasmita Triyani Hendrawati