Abstract: In recent months, China's A share showed a very large volatility with more than 1 000 shares falling by their 10 percent daily limit or increasing by their daily 10 percent limit usually on the same day. Is it possible to find stock market structural change point in advance based on historical information? For each component, a certain RuLSIF model is built. Taking the six dimension matrix as the sample, the non parametric density function ratio of the time series sample is estimated to be the structural change point of A stock market. Empirical results show that since the establishment of A shares, October 16 2014 has been the market structure mutation points. That is, beginning from that day, A-share market structure has undergone fundamental changes, to be very different from the market structure before. The model based on the sample data obtained from the sample forecast and the actual trend is consistent, and then the model can provide reference for the adjustment of the investment strategy in the actual investment.