Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Operations Research: International Conference Series
Adhy Prasetyo
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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

Found 1 Documents
Search

 1 
Estimation of the Value-at-Risk (VaR) Using the TARCH Model by Considering the Effects of Long Memory in Stock Investments Nurfadhlina Abdul Halim; Agus Supriatna; Adhy Prasetyo
Operations Research: International Conference Series Vol 1, No 1 (2020)
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i1.22

Abstract

Value at Risk (VaR) is one of the standard methods that can be used in measuring risk in stock investments. VaR is defined as the maximum possible loss for a particular position or portfolio in the known confidence level of a specific time horizon. The main topic discussed in this thesis is to estimate VaR using the TARCH (Threshold Autoregressive Conditional Heteroscedasticity) model in a time series by considering the effect of long memory. The TARCH model is applied to the daily log return data of a company's stock in Indonesia to estimate the amount of quantile that will be used in calculating VaR. Based on the analysis, it was found that with a significance level of 95% and assuming an investment of 200,000,000 IDR, the VaR using the TARCH model approach was 5,110,200 IDR per day.
Co-Authors Agus Supriatna Nurfadhlina Abdul Halim