Nilai Risiko Terkondisi pada Return Finansial Menggunakan Metode Copula Gumbel

Article History

Submited : December 20, 2020
Published : February 1, 2022

The calculation of VaR is assumed normal distribution while the conditions in the real world distribution conditions of the return value depends on the market conditions that occurred at the time. Thus, this makes VaR estimates invalid which results in portfolio risk occurring greater than the predetermined risk. Therefore, In this study, the estimated risk value uses the Conditional Value at Risk (CVaR), which measures the expected value depending on what is the worst percentage of the risk loss, and using Copula Gumbel to model financial return in the investment data of PT. Telkomunikasi Indonesia tbk and PT. XL Axiata tbk. for the period March 11, 2019 to March 10, 2020. In this study, the CVaR estimation results for the 99% confidence level is 0.231, while for the VaR estimate it is 0.192. This indicates that risk value with CVaR estimate is better able to show higher risk than VaR.

References

  1. Halim, Abdul. 2005. Analisis Investasi. Edisi Kedua. Jakarta: Salemba Empat.
  2. Jorion, Philippe. 2000. Value at Risk. Edisi kedua. USA: Mc GrawHill.
  3. Jogiyanto, Hartono. 1998. Teori Portofolio dan Analisis Investasi. Edisi Pertama. Yogyakarta: BPFE.
  4. Artzner,dkk. 1999. Coherent Measures of Risk. Mathematical Finance. 9(2): 203-228.
  5. Dharmawan, K. 2014. Estimasi Nilai Value At Risk Portofilio Menggunakan Metode T-Copula. Bali : Universitas Udayana.
  6. Yang, Insoon. 2015. Risk Management and Combinatorial Optimization for Large-Scale Demand Response and Renewable Energy Integration. Dissertation Engineering – Electrical Engineering and Computer Sciences Graduate Division, Berkeley: University of California.
  7. Zuhra, dkk. 2015. Estimasi Value At Risk Return Portofolio Menggunakan Metode Copula. Jurnal Statistika Terapan FMIPA Universitas Padjadjaran. Bandung: Universitas Padjadjaran.
  8. Damasari, Annisa. 2015. Estimasi Value at Risk (VaR) dengan Metode Simulasi Monte Carlo-Copula Gumbel. Skripsi Jurusan Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga. Yogyakarta.
  9. Hanafi, Mamduh M., dan Halim, Abdul. 2009. Analisis Laporan Keuangan. Yogyakarta: UPP STIM YKPN
  10. Nelsen, R. B. 2006. An Introduction to Copulas ,Springer, New York, 2nd edn.
  11. Embrechts, P., F. Lindskog, A. McNeil. 2001. Modeling Dependence with Copula and Application to Risk Management. Handbook of Heavy Tailed Distributions in Finance, ed. S, Rachev, San Diego: Elsevier.
  12. Darwis. 2016. Analisis Hubungan Dan Prediksi Indeks Harga Saham Gabungan Dengan Faktor Makroekonomi Melalui Pendekatan Copula. Thesis Jurusan Statistika FMIPA IPB. Bogor: IPB.
  13. Urysev, S., 2000. Conditional Value-at-Risk: Optimization Algorithms and Aplication. Financial Engineering News. University of Florida.
  14. Conover, W.J. 1971. Practical Nonparametric Statistics. New York: John Wiley and Sons.

Downloads

Download data is not yet available.
Fulltext
statcounter