AI algorithms development and implementation for the future world - Zhang, Yi Ting (Nanyang Technological University, 2021)
The development of the stock market has a history of more than 400 years. With the rapid growth of the financial market, the number of stock investors has become larger and more mature, and the prediction of stock price has always been the main concern of stock investors. Due to the high noise, dynamic, nonlinear and non-parametric characteristics of stock price, it is still a great challenge to predict the stock price accurately. But with the advance of big data and the development of Artificial Intelligence technology. It is gradually becoming possible to predict stock prices with greater accuracy. At present, more and more researchers adopt Artificial Intelligence technology to forecast the stock price. From the traditional Artificial Neural Network model to the Deep Learning model, and then to the present multiple models combined with each other for prediction, these technologies have been improved and widely used. In this project, technical analysis is mainly focused on using two different machine learning techniques (Support-Vector Machine and Long-Short Term Memory) to predict the closing price of Apple Inc. The results shows that LSTM model has the best prediction result with smaller value in difference compare to SVM model.