吉林快三Asset price prediction by CNN+LSTM
Prof. Yongzeng Lai, Wilfrid Laurier University, Canada
yongzeng laijiaoshou，xianrendepartment of mathematics, wilfrid laurier universityjiaoshou、boshishengdaoshi。2000nianmeiguojiazhoudaxueshuxueboshibiye，2000-2002nianzaijianadahuatieludaxuezuoboshihou。zhuyaocongshidashujufenxi，jinrongdingliangfenxi。zaiapplied mathematics and computation，insurance, mathematics and economics，computers & operations research，computational statistics & data analysisdengqikanfabiaolunwen20yupian。
prediction of asset prices is difficult due to the nature of asset prices. traditional statistical models and some basic machine learning as well as deep learning techniques were used in forecasting stock prices in the literature. in this talk, we will introduce our recent work on asset price prediction using some deep learning based techniques. various asset prices from different industries in both mature and emerging markets are selected to test the algorithms. our test results show that the convolutional neural network (cnn) and the long short-term memory (lstm) based algorithm outperforms other selected neural network based algorithms and arima type time series model.