This Author published in this journals
All Journal E-Jurnal Matematika
NABILA NUR JANNAH
Universitas Udayana

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

PENGGUNAAN SIMULASI MONTE CARLO DALAM ESTIMASI VALUE AT RISK (VaR) PORTOFOLIO YANG DIBENTUK DARI INDEKS HARGA SAHAM MULTINASIONAL NABILA NUR JANNAH; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 11 No 3 (2022)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2022.v11.i03.p381

Abstract

Investment is buying an asset that is expected in the future can be resold and get a high profit value. There are two factors that must be considered when you want to invest in stocks, namely the rate of return on stocks and risk factors. By forming a portfolio is expected to minimize a risk. Value at Risk (VaR) is a form of measurement of risk when making investments. In this study VaR will be calculated using the Monte Carlo Simulation method and the Historical method. This study aims to find out var portfolio estimates involving JCI and DJIA stock indices from two different countries as well as to find out the differences between VaR using Historical and VaR using Monte Carlo Simulations. From the stock index data obtained further determined the value of the parameters, namely the expected return and standard deviation values used to calculate the value of the VaR Portfolio, while the confidence increase used in this study was 99% and with a period of 1 or the next day. Based on the results of the VaR value study using the Monte Carlo Simulation method and the Historical method, the Historical method obtained results of 3,650,506 and 1,029,103. The results showed that VaR values using the Monte Carlo Simulation method got greater results than using the Historical method, because the Monte Carlo Simulation performed repeated iterations by including random number generators.