摘要：Shanghai composite index reflects the changes of stock prices, and the methods for various models to predict the stock index emerge one after another, and artificial intelligence is also widely used in various fields due to its stability and accuracy. In this paper, artificial intelligence is applied to Shanghai composite index to predict the stock index. A total of 3422 Shanghai composite indexes from January 1, 2005 to January 1, 2019 were collected, including five indexes: opening price, maximum price, closing price, minimum price and trading volume. Then MA, KDJ and MACD were selected as technical indexes, and their application methods and advantages in Shanghai composite index were analyzed in detail. In addition, in this paper, logistic regression and support vector machine (SVM) in artificial intelligence model were adopted to predict the ups and downs. Finally, it indicates that the support vector basis method based on radial basis is more suitable for stock index prediction model. In this paper, a framework of index prediction is provided by combining technical indicators with artificial intelligence.
其他摘要：Shanghai composite index reflects the changes of stock prices, and the methods for various models to predict the stock index emerge one after another, and artificial intelligence is also widely used in various fields due to its stability and accuracy. In this paper, artificial intelligence is applied to Shanghai composite index to predict the stock index. A total of 3422 Shanghai composite indexes from January 1, 2005 to January 1, 2019 were collected, including five indexes: opening price, maximum price, closing price, minimum price and trading volume. Then MA, KDJ and MACD were selected as technical indexes, and their application methods and advantages in Shanghai composite index were analyzed in detail. In addition, in this paper, logistic regression and support vector machine (SVM) in artificial intelligence model were adopted to predict the ups and downs. Finally, it indicates that the support vector basis method based on radial basis is more suitable for stock index prediction model. In this paper, a framework of index prediction is provided by combining technical indicators with artificial intelligence.
