Conference Proceedings

Transfer Learning for Financial Time Series Forecasting

Qi-Qiao He, Patrick Cheong-Iao Pang, Yain-Whar Si, Abhaya C Nayak, Alok Sharma

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer International Publishing | Published : 2019

Abstract

Time-series are widely used for representing non-stationary data such as weather information, health related data, economic and stock market indexes. Many statistical methods and traditional machine learning techniques are commonly used for forecasting time series. With the development of deep learning in artificial intelligence, many researchers have adopted new models from artificial neural networks for forecasting time series. However, poor performance of applying deep learning models in short time series hinders the accuracy in time series forecasting. In this paper, we propose a novel approach to alleviate this problem based on transfer learning. Existing work on transfer learning uses ..

View full abstract