Day ahead forecasting of FAANG stocks using ARIMA, LSTM networks and wavelets.
Skehin, Tom, Crane, MartinORCID: 0000-0001-7598-3126 and Bezbradica, Marija
(2018)
Day ahead forecasting of FAANG stocks using ARIMA, LSTM networks and wavelets.
In: The 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, 6-7 Dec 2018, Dublin, Ireland.
Abstract. Facebook Inc., Apple Inc., Amazon.com Inc., Net
ix Inc. and Alphabet Inc., known collectively as FAANG, are a group of the best performing tech stocks in recent years. In this study, we present linear
and non-linear methods for predicting the closing price of each stock
on the following day. We decompose each time series into component
series using wavelet methods and develop an novel ensemble approach to
improve forecast accuracy.