Financial Time Series Forecasting – A Deep Learning Approach
By Alexiei Dingli, Karl Sant Fournier. 2017
103 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Management Science and Operations Research, Economics & Operations Research, Signal Processing, Time-Series & Forecasting
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In Computer Vision and Pattern Recognition
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In Time-Series & Forecasting
Citations in the corpus
- Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “The authors of [123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 114] used S&P500 as their dataset.”
- Applications of deep learning in stock market prediction: recent progress (2020, background): “(2017b); Zhong & Enke (2017); Baek & Kim (2018); Chung & Shin (2018); Hollis et al. (2018); Hossain et al. (2018); Liu & Wang (2019); Pang et al.”
- Text embedding models can be great data engineers (2025, unknown): “Data engineering pipelines are fundamental components for enabling predictive analytics on time series data in several areas such as energy [38], healthcare [3] and finance [6].”