VALUE AT RISK ANALYSIS ON BLUE CHIP STOCKS PORTFOLIO WITH GAUSSIAN COPULA
Abstract
Value at Risk (VaR) is a risk measurement tool to calculate the estimated maximum investment loss with a certain confidence level and period. VaR calculations using financial data are often not normally distributed, so the copula method is used, which is flexible on the assumption of normality on stock return data. Previous research discussed Gaussian copula using stocks from the telecommunications sector. In this research, using Gaussian copula on Blue Chip stocks. Blue Chip stocks have a good reputation and have a stable growth rate so they have a lower risk. Therefore, the research objective is to analyze the VaR portfolio of Blue Chip stock with Gaussian copula. This research uses the daily stock closing prices of BBNI and BBTN from November 2, 2020 to October 27, 2022. The analysis results suggested that a VaR portfolio using Gaussian copula with a confidence level of 90%, 95%, and 99%, respectively are 2.24%, 2.88%, and 4.02%. The value shows the percentage of investment risk that may be obtained in the next one-day period. This result also indicates that the higher the confidence level, the greater the VaR.
Downloads
References
I. Hendarsih and S. Harjunawati, “Penggolongan Saham Blue Chip Berdasarkan Kapitalisasi Pasar Pada Bursa Efek Indonesia Tahun 2017-2020,” J. Akrab Juara, vol. 5, no. 2, pp. 115–133, 2020.
X. Wang, J. Cai, and K. He, “EMD Copula based Value at Risk Estimates for Electricity Markets,” Procedia Comput. Sci., vol. 55, pp. 1318–1324, 2015.
R. E. Caraka, H. Yasin, W. Sugiarto, Sugiarto, and K. M. Ismail, “Time Series Analysis Using Copula Gauss And AR(1)-N.GARCH(1,1),” Media Stat., vol. 9, no. 1, pp. 1–13, 2016.
K. Byun and S. Song, “Value at Risk of portfolios using copulas,” vol. 28, no. 1, pp. 59–79, 2021.
F. Wang et al., “Copula-Based Drought Analysis Using Standardized Precipitation Evapotranspiration Index : A Case Study in the Yellow River Basin, China,” Water, vol. 11, pp. 1–20, 2019.
H. Hidayati, K. Dharmawan, and I. W. Sumarjaya, “Estimasi Nilai Conditional Value at Risk Menggunakan Fungsi Gaussian Copula,” E-Jurnal Mat., vol. 4, no. 4, pp. 188–194, 2015.
P. O. J. Kelliher et al., “Operational risk dependencies,” Br. Actuar. J., vol. 25, pp. 1–21, 2020.
N. N. Jannah, K. Dharmawan, and L. P. I. Harini, “Penggunaan Simulasi Monte Carlo dalam Estimasi Value at Risk (VaR) Portofolio yang dibentuk dari Indeks Harga Saham Multinasional,” E-Jurnal Mat., vol. 11, no. 3, pp. 199–202, 2022.
A. M. Telussa, E. R. Persulessy, and Z. A. Leleury, “Penerapan Analisis Korelasi Parsial untuk Menentukan Hubungan Pelaksanaan Fungsi Manajemen Kepegawaian dengan Efektivitas Kerja Pegawai,” Barekeng J. Ilmu Mat. dan Terap., vol. 7, no. 1, pp. 15–18, 2013.
Q. R. Sartika, T. Widiharih, and M. A. Mukti, “Value at Risk in Stock Portfolio Using T-Copula: Case Study of PT. Indofood Sukses Makmur, Tbk. and Bank Mandiri (Persero), Tbk.,” Media Stat., vol. 12, no. 2, pp. 175–187, 2019.
O. W. Ningrum, Tarno, and D. A. I. Maruddani, “Perhitungan Value At Risk Pada Portofolio Saham Menggunakan Copula,” J. Gaussian, vol. 6, no. 2, pp. 231–240, 2017.
C. Li, V. P. Singh, and A. K. Mishra, “A bivariate mixed distribution with a heavy-tailed component and its application to single-site daily rainfall simulation,” Water Resour. Res., vol. 49, pp. 767–789, 2013.
N. C. Dzupire, P. Ngare, and L. Odongo, “A copula based bi-variate model for temperature and rainfall processes,” Sci. African, vol. 8, 2020.
I. Lisnawati and R. Subekti, “Estimasi Conditional Value at Risk (CVaR) Pada Portofolio Menggunakan Copula Bersyarat,” J. Kaji. dan Terap. Mat., vol. 7, no. 3, pp. 64–72, 2018.
I. P. Sanggup, N. Satyahadewi, and E. Sulistianingsih, “Perhitungan Nilai Ekspektasi Return dan Risiko dari Portofolio dengan Menggunakan Mean-Variance Efficient Portfolio,” Bimaster, vol. 03, no. 1, pp. 51–56, 2014.
R. I. Lestari, A. Tawe, Nurman, Z. Ruma, and Anwar, “Optimalisasi Portofolio Saham Blue Chips yang Terdaftar di Bursa Efek Indonesia dengan Menggunakan Model Markowitz di Era Pandemi Covid-19,” Forum Ekon. J. Ekon. Manaj. dan Akunt., vol. 24, no. 3, pp. 618–623, 2022.
X. Wang, D. Xie, J. Jiang, X. Wu, and J. He, “Value-at-Risk Estimation with Stochastic Interest Rate Models for Option-Bond-Portfolios,” Financ. Res. Lett., vol. 21, pp. 10–20, 2017.
A. Najiha, E. T. Herdiani, and G. M. Tinungki, “The Application of Gumbel Copula to Estimate Value at Risk with Backtesting in Telecommunication Stock,” Barekeng J. Ilmu Mat. dan Terap., vol. 17, no. 1, pp. 245–252, 2023.
E. Sulistianingsih, D. Rosadi, and Abdurakhman, “Credible Delta-Gamma-Normal Value-at-Risk for European Call Option Risk Valuation,” Eng. Lett., vol. 29, no. 3, pp. 1026–1034, 2021.
E. Sulistianingsih, D. Rosadi, and Abdurakhman, “Credible Delta Normal Value at Risk for Risk Evaluation of European Call Option,” Ind. Eng. Manag. Syst., vol. 22, no. 1, pp. 20–30, 2023.
Copyright (c) 2023 Tiffany Ardhitha, Evy Sulistianingsih, Neva Satyahadewi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this Journal agree to the following terms:
- Author retain copyright and grant the journal right of first publication with the work simultaneously licensed under a creative commons attribution license that allow others to share the work within an acknowledgement of the work’s authorship and initial publication of this journal.
- Authors are able to enter into separate, additional contractual arrangement for the non-exclusive distribution of the journal’s published version of the work (e.g. acknowledgement of its initial publication in this journal).
- Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their websites) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.
1.gif)
