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AdaBoost-LSTM Ensemble Learning for Financial Time Series Forecasting · Study

WorkAdaBoost-LSTM Ensemble Learning for Financial Time Series Forecasting

Shaolong Sun2018

Work2018

AdaBoost-LSTM Ensemble Learning for Financial Time Series Forecasting

Shaolong Sun · Yunjie Wei · Shouyang Wang

62 citations·0/0 files stored·Lecture notes in computer science

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Stock Market Forecasting Methods Forecasting Techniques and Applications Time Series Analysis and Forecasting

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References

2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm 1998Neural network forecasting of the British Pound/US Dollar exchange rate 2004A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates 2015Forecasting exchange rate using deep belief networks and conjugate gradient method 2015A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting 2002Forecasting daily foreign exchange rates using genetically optimized neural networks 2009Forecasting exchange rates with a large Bayesian VAR 2012Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization

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2019Research on Quantitative Investment Strategies Based on Deep Learning 2022Decision Fusion for Stock Market Prediction: A Systematic Review

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Details

Year2018

Typeother

Published2018-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations62

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1007/978-3-319-93713-7_55

openalex_workW2807796723

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