Abstract: Value at risk is a statistical risk management technique that monitors and quantifies the risk level associated with an investment portfolio. The maximum amount of loss over a specified time horizon with a given confidence level is usually measured by this technique. The presented study aimed at estimating the conditional value at risk for Tehran stock market data through two steps. First the volatility parameter is estimated with a generalized-Quasi-Maximum Likelihood Estimator (gQMLE) and then empirical quantile of the residuals is estimated using the estimated rescaled innovations.