Conditional Value-at-Ｒisk ( CVaＲ) model developed recently is a powerful mathematical tool to measure financial risk． By constructing on the risk optimization and risk hedging models based on the CVaＲ kernel estimator and designing an optimization algorithm to solve these models，this paper accomplishes the goal that financial risk estimation and risk management are implemented at the same time． These models are applied to Chinese A stock market，and the following conclusions are obtained: nonparametric kernel estima_x005ftion method can capture the tail feature of the risk factor distribution and give more accurate risk estimation results． The risk optimization model based on CVaＲ kernel estimator can find out the true minimum risk and corresponding portfolio． Compared with Variance-Covariance method and Cornish-Fisher expansion of CVaＲ， the risk hedging effect based on CVaＲ kernel estimator is the best．