Stock quantitative trading, that is, all the stock market stock information, such as the stock's historical data, turnover historical data, stock fundamentals historical data, index historical data, etc., all into the computer, big data analysis, and then according to the big data to select the highest success rate of speculation program, and designed into the computer automated trading mode, known as quantitative trading. The so-called quantitative trading, refers to the advanced mathematical model to replace the human subjective judgment, while using computer technology from the huge sea of historical data can bring excessive returns of a variety of "probability" of events to develop strategies, greatly reducing the impact of investors' emotional fluctuations, to avoid the market in the case of extreme frenzy or pessimism to make Avoid making irrational investment decisions when the market is extremely frenzied or pessimistic. Quantitative stock selection is the use of quantitative methods to select a portfolio of stocks, the expectation that the portfolio of stocks can be obtained beyond the benchmark rate of return investment behavior, research shows that sector and industry rotation in the trading of institutional investors is the most profitable profit model is based on the industry level of cyclical and defensive rotation allocation, which is also the most common strategy used by institutional investors. In addition, cyclical stocks perform better during periods of expansionary monetary policy, while supporting non-cyclical sectors in a tightening environment. Sector return spreads differ significantly between expansionary and tightening policies.