In recent years, with the rapid development of face recognition, speech recognition, autonomous driving and many other fields, artificial intelligence has gradually been pushed to the development wave. Then when investment meets artificial intelligence, there is an emerging field - quantitative finance. A very important application area of artificial intelligence is forecasting. Based on today's data and historical data, future economic trends can be judged. In the field of finance and investment, artificial intelligence technology can predict the price trend of stocks and investment targets, so that computers can make decisions for humans and realize automated transactions to obtain profits.
Recently, a team led by Master Zeng Kai from the Intelligent Information Processing Laboratory of Northwestern University participated in the China (Hengqin) International University Quantitative Finance Competition hosted by the Shenzhen Research Institute of Peking University and the Shenzhen Research Institute of Tsinghua University , and won the finals in the competition. The good results of the third prize. Among them, Columbia University, National University of Singapore, Hong Kong University, Tsinghua University, Peking University and other top universities at home and abroad have advanced to the semi-finals. In the final stage, they competed fiercely with other teams and defended, and finally from 15 stand out from the team.
After the competition, the 2018 China (Hengqin) Quantitative Finance Summit Forum was held, in which Zhou Xunyu, a professor at Columbia University, put forward some new quantitative finance ideas in the summit forum lecture, such as displaying the historical price information of stocks through graphics and images. Then use the convolutional neural network for feature extraction, and then classify the stock to determine whether it is a good stock through the method of image extraction features. This method is different from the traditional analysis based on historical data. With statistical methods, ideas are novel and deeply inspired.
The academic team of intelligent information processing of Northwestern University has many years of research foundation in the field of artificial intelligence and machine learning. By applying its algorithm ideas to the investment field, there will be great achievements. For example, when we apply the clustering algorithm to stock clustering, can it also be realized? A classification effect that identifies good stocks. These new problems and research methods are waiting for everyone to continue to explore. On the road ahead, we need to continue to work hard and make persistent efforts. I wish the laboratory to climb the peak of scientific research in the future.