Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately

Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately

Abstract Stocks are an attractive investment option because they can generate large profits compared to other businesses. The movement of stock price patterns in the capital market is very dynamic. Therefore, accurate data modeling is needed to forecast stock prices with a low error rate. Forecastin...

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Bibliographic Details
Main Authors: Armin Lawi, Hendra Mesra, Supri Amir
Format: Article
Language:English
Published: SpringerOpen 2022-07-01
Series:Journal of Big Data
Subjects:
Forecasting methods
Time-series forecasting
Deep Learning
Stock price
Recurrent Neural Network
Long-Short Term Memory
Online Access:https://doi.org/10.1186/s40537-022-00597-0

Internet

https://doi.org/10.1186/s40537-022-00597-0

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