Value-at-Risk and Average Value-at-Risk are tow important risk measures based on statistical methoeds that used to measure the market's risk with quantity structure. Recently, linear regression models such as least squares and quantile methods are introduced to estimate these risk measures. In this paper, these two risk measures are estimated by using omposite quantile regression. To evaluate the performance of the proposed model with the other models, a simulation study was conducted and at the end, applications to real data set from Iran's stock market are illustarted.