Forecasting stock price movement: new evidence from a novel hybrid deep learning model

Forecasting stock price movement: new evidence from a novel hybrid deep learning model

Purpose – This study explores whether a new machine learning method can more accurately predict the movement of stock prices. Design/methodology/approach – This study presents a novel hybrid deep learning model, Residual-CNN-Seq2Seq (RCSNet), to predict the trend of stock price movement. RCSNet inte...

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Bibliographic Details
Main Authors: Yang Zhao, Zhonglu Chen
Format: Article
Language:English
Published: Emerald Publishing 2022-05-01
Series:Journal of Asian Business and Economic Studies
Subjects:
stock price movement
rcsnet
arima
cnn
lstm
s&p 500 index
c52
g11
g12
Online Access:https://www.emerald.com/insight/content/doi/10.1108/JABES-05-2021-0061/full/pdf?title=forecasting-stock-price-movement-new-evidence-from-a-novel-hybrid-deep-learning-model

Internet

https://www.emerald.com/insight/content/doi/10.1108/JABES-05-2021-0061/full/pdf?title=forecasting-stock-price-movement-new-evidence-from-a-novel-hybrid-deep-learning-model

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