slot gacor slot gacor hari ini slot gacor 2025 demo slot pg slot gacor slot gacor
ESTIMASI RISIKO PORTOFOLIO SAHAM PERUSAHAAN PERKEBUNAN DI BURSA EFEK INDONESIA MENGGUNAKAN VALUE AT RISK NON-NORMAL | Ikhsan | Jurnal Gaussian skip to main content

ESTIMASI RISIKO PORTOFOLIO SAHAM PERUSAHAAN PERKEBUNAN DI BURSA EFEK INDONESIA MENGGUNAKAN VALUE AT RISK NON-NORMAL

*Aulia Ikhsan  -  Jurusan Agribisnis, Fakultas Pertanian, Universitas Sultan Ageng Tirtayasa, Indonesia
Tatang Sutisna orcid scopus  -  Jurusan Agribisnis, Fakultas Pertanian, Universitas Sultan Ageng Tirtayasa, Indonesia
Siti Widiati orcid  -  Jurusan Agribisnis, Fakultas Pertanian, Universitas Sultan Ageng Tirtayasa, Indonesia
Open Access Copyright 2023 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
Stock investment portfolio aims to minimize the investment risk. However, problems of the portfolio formation are determining funds allocation for each stock and measuring its risk. Fund allocation is determined using the Mean-Variance Efficient Portfolio method, while risk measurement is carried out using Value at Risk (VaR). Nevertheless, problem on VaR is determining a fit distribution which would be involved to obtain quantile values at certain probability. This study discusses way of funds allocation determination and VaR value calculation that is aimed to analyze their impact in estimating the VaR value. The study used stock price return rate data of plantation companies listed on Indonesia Stock Exchange such as Astra Agro Lestari Tbk. (AALI), BISI International Tbk. (BISI), and PP London Sumatra Indonesia Tbk. (LSIP). The result showed BISI stock has high volatility so that its funds allocation is relatively smaller. The distribution identified for portfolio return rate is Logistics Distribution with the estimated parameters  0.0001187447 and 0.008810698. Portfolio VaR value at the 95% confidence level is -0.02582382. We conclude the determination of funds allocation does not minimize risk and the calculation of VaR with distributions do not match the data result a relatively higher VaR value.
Fulltext View|Download
Keywords: Value at Risk; Mean-Variance Efficient Portfolio; Plantation Stock; Logistics Distribution.

Article Metrics:

  1. Anam, K. et.al., 2020. Pengukuran Value at-Risk pada Portofolio Obligasi dengan Metode Varian-Kovarian. Jurnal Gaussian Vol. 9 No. 4 ISSN: 2339-2541
  2. Balakrishnan, N., 1992. Handbook of The Logistic Distribution. Marcel Dekker, Inc: New York
  3. Biswas, D., 2015. The Effect of Portfolio Diversification Theory: Study on Modern Portfolio Theory of Stock Investment in The National Stock Exchange. Journal of Commerce and Management Thought Vol.6 DOI: 10.5958/0976-478X.2015.00027.0
  4. Bohdalová, M., and Greguš., M., 2015. Estimating Value-at-Risk Based on Non-Normal Distributions. CBU international Conference Proceedings Vol. 3 DOI: 10.12955/cbup.v3.601
  5. Byun, K., and Song, S., 2021. Value at Risk of Portfolios Using Copulas. Communication for Statistical Applications and Methods 28:59-79 https://doi.org/10.29220/CSAM.2021.28.1.059
  6. Casella, G., and Berger, R.L., 2002. Statistical Inference. Second Edition. Duxbury Thomson Learning: USA
  7. Cullen, A.C., and Frey, H.C., 1999. Probabilistic Technique in Exposure Assessment. First Edition. Plenum Publishing Co
  8. Daniel, W.W., 1990. Applied Nonparametric Statistics. Second Edition. PWS-KENT Publishing Company: Boston
  9. Delignette-Muller, M.L., and Dutang, C., 2015. fitdistrplus: An R Package for Fitting Distributions. Journal of Statistical Software Vol. 64 https://doi.org/10.18637/jss.v064.i04
  10. Elton, E.J. et.al., 2013. Modern Portfolio Theory and Investment Analysis. Ninth Edition. John Wiley & Sons, Inc: New York
  11. Hartono, J., 2013. Teori Portofolio dan Analisis Investasi. Edisi Ketujuh. BPFE Yogyakarta: Yogyakarta
  12. He, Y., 2015. A Probabilistic Model of Benefit-Cost Analysis for Highway Construction Projects [Thesis]. Indiana: Purdue University
  13. Hermansah, 2017. Estimasi Value at Risk dengan Distribusi Normal untuk Memprediksi Return Investasi. Jurnal Mercumatika Vol. 1 No. 2 ISSN: 2548-1819
  14. Johnson, R. A., and Wichern, D. W., 2007. Applied Multivariate Statistical Analysis. Sixth Edition. Pearson Prentice Hall: New Jersey
  15. Jorion, P., 2001. Value At Risk: The New Benchmark for Managing Financial Risk. Second Edition. The McGraw-Hill Companies, Inc: Boston
  16. Maruddani, D.I.A, dan Purbowati, A. 2009. Pengukuran Value at Risk pada Aset Tunggal dan Portofolio dengan Simulasi Monte Carlo. Jurnal Media Statistika. Vol. 2(2): 93-104. Undip: Semarang
  17. Oktafiani, H.E. et.al., 2017. Penerapan Model Indeks Tunggal untuk Optimalisasi Portofolio dan Pengukuran Value at Risk dengan Variance Covariance. Jurnal Gaussian Vol. 6 No. 1 ISSN: 2339-2541
  18. Pracoyo, A., dan Muslich, M., 2006. Studi Pengukuran Value at Risk pada Distribusi Return Saham yang Bersifat Leptokurtosis: Studi Kasus Saham ASII, ISAT, SMDR, dan UNVR [Tesis]. Depok: Universitas Indonesia
  19. Purcell, E.J., dan Varberg, D., 1987. Kalkulus Dan Geometri Analitis. Edisi kelima. Erlangga: Jakarta
  20. Searle, S.R., 1982. Matrix Algebra Useful for Statistics. John Wiley & Sons: New York
  21. Tupan, L.P. et.al., 2013. Pengukuran Value at Risk Pada Aset perusahaan dengan Metode Simulasi Monte Carlo. Jurnal MIPA Unsrat Vol. 2 No. 1 http://ejournal.unsrat.ac.id/index.php/jmuo

Last update:

No citation recorded.

Last update:

No citation recorded.