With the rapid urbanization and motorization，a few cities in China join the line to regulate private car ownership and the policy performance should be systematically evaluated．With some statistical learning methods like Principal Component Analysis (PCA) ，Hurst Index，Gaussian Process Ｒegression (GPＲ) and the econometric method like Difference-in-Difference (DID) and OLS，this paper tries to discover the main characteristics of the auction market by formulating a linear equation of key variables of Shanghai license quota auction market，changing rate and prediction of the auction prices，in order to evaluate the performance of policy instruments like the released quota and the price cap．The PCA analysis shows that there is a positive bidirectional relationship and a positive incentive effect between the quota and the price in the auction market．Meanwhile Hurst Index analysis shows the changing rate of the prices will return to the mean value．It further shows with three comparative groups by DID that the auction regulation slows down the increase of private vehicles at an annual rate of around 27% ～ 36% and the quota increment significantly makes the auction market stable by decreasing both the price volatility and the bidders’competition.Finally，with the prediction precision worsening with GPＲ after 2014，the improvement of the regulation such as deregulating the price cap hasalso been discussed to give some light on enhancing the implication of quota strategies.