Stock index forecasting based on multivariate empirical mode decomposition and temporal convolutional networks

Another look at measures of forecast accuracy

Rob J. Hyndman, Anne B. Koehler · International Journal of Forecasting · 2006 · 5K citations

Forecasting Methodology, Probabilistic Forecasting, Engineering +8

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Shaojie Bai, J. Zico Kolter, Vladlen Koltun · arXiv (Cornell University) · 2018 · 4.3K citations · Full text

Structured Prediction, Engineering, Machine Learning +20

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

Wei Bao, Jun Yue, Yulei Rao · PLoS ONE · 2017 · 1K citations · Full text

Engineering, Machine Learning, Autoencoders +18

Multivariate empirical mode decomposition

Naveed ur Rehman, D. Mandic · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2009 · 848 citations

Numerical Analysis, Multivariate Extensions, Engineering +14

Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies

Eunsuk Chong, Chulwoo Han, Frank C. Park · Expert Systems with Applications · 2017 · 803 citations · Full text

Intelligent Forecasting, Deep Neural Networks, Engineering +11