Research on Stock Price Prediction Based on Pattern Recognition
The method of time series data analysis based on pattern recognition has attracted wide attention in the fields of economics,statistics,and machine learning due to its ability to reveal complex and nonlinear stock price patterns.A heuristic based template called the"Double Bottoms",which transfers a one-dimensional stock price time series to a two-dimensional template,and identifies time segments with high similarity to the template as signals which can predict future market price increments.Experimental results show that this method can generate positive returns and has a certain predictive ability for future stock price movements.
NETL
NSTL
万方数据
维普
