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Predicting Stock Price Using Two-Stage Machine Learning Techniques · Study

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ArticlePredicting Stock Price Using Two-Stage Machine Learning Techniques

Lan Li2020

Article2020

Predicting Stock Price Using Two-Stage Machine Learning Techniques

Lan Li · Wei Chen

53 citations·0/0 files stored·Computational Economics

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1965The Behavior of Stock-Market Prices 2011Twitter mood predicts the stock market 2003Financial time series forecasting using support vector machines 2003Constructivist and Ecological Rationality in Economics 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies 2011Using artificial neural network models in stock market index prediction

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2022Stock Market Forecasting Using the Random Forest and Deep Neural Network Models Before and During the COVID-19 Period 2022AEI-DNET: A Novel DenseNet Model with an Autoencoder for the Stock Market Predictions Using Stock Technical Indicators 2021Quantum Computing and Deep Learning Methods for GDP Growth Forecasting 2022Poly-linear regression with augmented long short term memory neural network: Predicting time series data 2024A bibliometric literature review of stock price forecasting: From statistical model to deep learning approach

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Year2020

Typearticle

Published2020-07-20

VenueComputational Economics

ISSN-L0927-7099

Languageen

Citations53

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1007/s10614-020-10013-5

openalex_workW3045338483

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