Speaker:Yongzeng Lai

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.

Time:December20th15:00

Venue：Lecture Hall,Nanjie, School of Mathematics and Statistics

Speaker Introduction:

Yongzeng Lai is a professor in the Department of Mathematics, Wilfrid Laurier University, Canada. He has presided over many NSFC projects in Canada. His main research fields include financial mathematics (pricing and risk management of derivatives, financial calculation, portfolio optimization, application of stochastic analysis in finance and insurance), application of differential equations in finance and economics, Monte Carlo and Quasi Monte Carlo simulation methods and applications. He has published more than 50 papers in international journals and conference proceedings, such as Automatica, Journal of Computational Finance, Computers & Operations Research, Insurance Mathematics and Economics, Economic Modeling, Nonlinear Analysis, Computational Statistics & Data Analysis.