VALUE-AT-RISK WITH VARIABILITY EFFECT OF PARAMETER

• Main Author: WINDRAWAN FARHAN SAPUTRA (NIM : 10108029); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, RIZKY
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/17063
• Institution: Institut Teknologi Bandung

Measuring risk needs to be done for anticipating the loss of the changing price (return). The measuring risk of maximum loss with a probability level of the changing price can use Value-at-Risk. The focus on this thesis is the effect variability of parameter on Value-at-Risk. Model Time Series is used for calculating the value of Value-at-Risk prediction. <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> This thesis will measure the maximum loss of return gold price which is assumed following normal distribution. Model Autoregressive(1) and model Autoregressive Conditional Heteroscedastic(1) are used to determine the value of Value at Risk prediction. From the result of the value of Value-at-Risk prediction, the effect variability of parameter of model Time Series such as bias and mean square error can be seen. The value of bias and mean square error is the orde O(n-1).