BibTex Citation Data :
@article{Medstat2499, author = {Di Asih Maruddani and Ari Purbowati}, title = {PENGUKURAN VALUE AT RISK PADA ASET TUNGGAL DAN PORTOFOLIO DENGAN SIMULASI MONTE CARLO}, journal = {MEDIA STATISTIKA}, volume = {2}, number = {2}, year = {2009}, keywords = {}, abstract = { Value at Risk (VaR) is the established standard for measuring market risk. VaR measures the worst expected loss under normal market conditions over a specific time interval at a given confidence level. A VaR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage). The Monte Carlo simulation method calculates the change in the value of positions by using a random sample generated by price scenarios. Instead of using the past value of risk factors, Monte Carlo simulation generates models to estimate the risk factors from past portfolio returns by specifying the distributions and their parameters. Using these distributions and parameters, we can generate thousands of hypothetical scenarios for risk factors and, finally, we can determine future prices or rates based on hypothetical scenarios. VaRs can be derived from the cumulative distribution of future prices or rates for given confidence levels. In this paper, we calculate VaR at PT Astra International Tbk., PT Telekomunikasi Tbk., and the portfolio of the two assets. PT. Astra International Tbk has higher VaR than PT. Telekomunikasi Tbk. The VaR of a portfolio has lower result than VaR of each single asset. Keywords : Value at Risk, Time Period, Confidence Level, Monte Carlo Simulation. }, issn = {2477-0647}, pages = {93--104} doi = {10.14710/medstat.2.2.93-104}, url = {https://ejournal.undip.ac.id/index.php/media_statistika/article/view/2499} }
Refworks Citation Data :
Value at Risk (VaR) is the established standard for measuring market risk. VaR measures the worst expected loss under normal market conditions over a specific time interval at a given confidence level. A VaR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage). The Monte Carlo simulation method calculates the change in the value of positions by using a random sample generated by price scenarios. Instead of using the past value of risk factors, Monte Carlo simulation generates models to estimate the risk factors from past portfolio returns by specifying the distributions and their parameters. Using these distributions and parameters, we can generate thousands of hypothetical scenarios for risk factors and, finally, we can determine future prices or rates based on hypothetical scenarios. VaRs can be derived from the cumulative distribution of future prices or rates for given confidence levels. In this paper, we calculate VaR at PT Astra International Tbk., PT Telekomunikasi Tbk., and the portfolio of the two assets. PT. Astra International Tbk has higher VaR than PT. Telekomunikasi Tbk. The VaR of a portfolio has lower result than VaR of each single asset.
Keywords : Value at Risk, Time Period, Confidence Level, Monte Carlo Simulation.
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