Analisi Resiko Portofolio Menggunakan Value at Risk dengan Metode Variansi Kovaransi dan Simulasi Historis

Authors

  • Norinda Supriyani Program Studi Matematika, Fakultas Sains dan Teknologi Terapan, Universitas Ahmad Dahlan Yogyakarta
  • Sugiyarto Sugiyarto Program Studi Matematika, Fakultas Sains dan Teknologi Terapan, Universitas Ahmad Dahlan Yogyakarta

DOI:

https://doi.org/10.26555/konvergensi.v6i1.19546

Keywords:

Portofolio, Variansi Kovaransi, VaR

Abstract

Resiko merupakan sesuatu yang ditanggung seseorang dalam melakukan aktifitas. Demikian juga  investor yang melakukan penanaman modal (investasi) pasti akan memperhitungkan  resiko yang terjadi akibat dari investasinya. Oleh karena itu, Investor perlu mengetahui cara menghitung resiko agar dapat mengambil tindakan yang tepat untuk portofolionya, sehingga mereka dapat memperhitungkan tingkat resiko yang mungkin diperoleh. Salah satu cara menghitung nilai resiko adalah dengan Value at Risk (VaR). Makalah ini menyajikan perhitungan VaR, dengan menggunakan metode analisa  variansi kovariansi.  Berdasarkan  metode ini , nilai resiko dipengaruhi oleh faktor harga pasar saham, volatilitas harga saham, periode waktu, dan tingkat kepercayaan yang digunakan. Asumsi yang digunakan pada metode ini adalah return berdistribusi normal.

References

C. Butler, Mastering Value at Risk: A step-by-step guide to understanding and applying VaR. Financial Times/Prentice Hall, 1999.

K. Dowd, An introduction to market risk measurement. John Wiley & Sons, 2003.

H. Mausser and D. Rosen, “Beyond VaR: from measuring risk to managing risk,†in Proceedings of the IEEE/IAFE 1999 Conference on Computational Intelligence for Financial Engineering (CIFEr)(IEEE Cat. No. 99TH8408), 1999, pp. 163–178.

C. Gourieroux and J. Jasiak, “Value at risk,†in Handbook of Financial Econometrics: Tools and Techniques, Elsevier, 2010, pp. 553–615.

T. Eduardus, “Analisis investasi dan manajemen portofolio,†Yogyakarta PT. BPFE, 2001.

P. Jorion, Value at risk: the new benchmark for managing financial risk. The McGraw-Hill Companies, Inc., 2007.

C. E. Heckler, “Applied multivariate statistical analysis.†Taylor & Francis, 2005.

J. Klett, Applied multivariate analysis. New York: McGraw-Hill, 1972.

H. Anton, P. Silaban, and I. N. Susila, Aljabar Linear Elementer. Erlangga, Jakarta, 1987.

H. Anton, “Aljabar Linier Elementer Edisi Ketiga,†Terjem. Pantur Silab. dan I. Nyoman Susila. Penerbit Erlangga, Jakarta, 1991.

Downloads

Published

2019-04-04

Issue

Vol. 6 No. 1 (2019)

Section

Articles

License

Authors who publish with this journal agree to the following terms:

1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons  Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

 

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 2.0 Generic License.