The Study of Value-At-Risk Calculation and Back-testing Using the ARMA-GARCH Model Based on Stock Returns: An Overview

Stocks are investment instruments that provide returns but tend to be risky. The most important component of investing is volatility, where volatility identical the standard conditional deviation stock price return. thing in addition return a risk. Value-at-Risk (VaR) statistical method estimating maximum losses. To evaluate quality VaR estimates, models should always back-tested with appropriate methods. Back-testing procedure which actual gains and losses systematically compared estimates. goal study was estimate Autoregressive Moving Average-Generalized Conditional Heteroscedastic (ARMA-GARCH) model determine back-testing. ARMA combination AR MA models, while GARCH time series symmetrical properties. this systematic browsing libraries. Systematic library tracing an attempt identify, evaluate, interpret all research relevant particular phenomenon.