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Tresno Sayekti Nuryanto
Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro

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HISTORICAL SIMULATION UNTUK MENGHITUNG VALUE AT RISK PADA PORTOFOLIO OPTIMAL BERDASARKAN SINGLE INDEX MODEL MENGGUNAKAN GUI MATLAB (Studi Kasus: Kelompok Saham JII Periode Juni - November 2017) Tresno Sayekti Nuryanto; Alan Prahutama; Abdul Hoyyi
Jurnal Gaussian Vol 7, No 4 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v7i4.28869

Abstract

The essence of investment is a placement of a number of funds at one time in hope of gaining profits in the future. One of the most traded forms of investment is stocks. When investing in stocks, investors often run the risk of loss. This loss risk can be overcome by forming a portfolio consisting of several shares. To form an optimal portfolio, investors must first determine an efficient portfolio that produces a certain level of profit with the lowest risk, or a certain level of risk with the highest level of profit. One method for determining the optimal portfolio is to use the Single Index Model method. Whereas to calculate Value at Risk (VaR) using the Historical Simulation method. In this study, researcher used data from the daily closing price of shares incorporated in the Jakarta Islamic Index (JII) stock group in the period of June - November 2017. The shares which will be used were 9 shares in the JII stock group. According to the research result, there are three stocks that go into an optimal portfolio that is SMGR, UNTR, and KLBF with the value of each of its shares respectively by 48,54%, 46,18%, and 5,28%. While the value of the Value at Risk with initial capital of Rp100.000.000, 1 day holding period and a trust level of 95% for optimal portfolio and each stock that goes into optimal portfolio amounted Rp2.090.283, Rp2.258.600, Rp3.403.000, and Rp2.564.200. Keywords: Share, Portofolio, Single Index Model, Value at Risk, Historical Simulation, JII.