題目：Asset price prediction by CNN+LSTM

主講人：Prof. Yongzeng Lai, Wilfrid Laurier University, Canada

講座時間：2019年12月17日（周二）下午13:50

講座地點：金融學(xué)院422會議室

主講人簡介：

Yongzeng Lai教授,，現(xiàn)任Department of Mathematics, Wilfrid Laurier University教授、博士生導(dǎo)師,。2000年美國加州大學(xué)數(shù)學(xué)博士畢業(yè),，2000-2002年在加拿大滑鐵盧大學(xué)做博士后,。主要從事大數(shù)據(jù)分析,，金融定量分析。在Applied Mathematics and Computation,，Insurance, Mathematics and Economics,，Computers & Operations Research,，Computational Statistics & Data Analysis等期刊發(fā)表論文20余篇。

Abstract

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.