Time series
Team Members: Amy Lim Zhi Ting, Ang Kai Chao, Jerome Neo, Liao Tian Chang, Lye Jian Wen, Shriya Saxena
As part of our course project, we worked on time series models that can help predict the closing stock prices for Apple stocks. We explored statistical methods as well as recurrent neural networks. We started off with (1) K-nearest neigbours, then we worked with (2) Auto Regressive Integrated Moving Average (ARIMA) and lastly, (3) Long Short-Term Memory. For each model we built, we compared the periods in which the models are trained/test on. More specifically, given a 5-year period vs 7-year period. Next, we compared the absolute the number of points in which the models are given to train/test on. We compared 30 vs 35 data points.
The following link is a video of our final project presention.