Cargando…
Data science approach to stock prices forecasting in Indonesia during Covid-19 using Long Short-Term Memory (LSTM)
BACKGROUND: Stock market process is full of uncertainty; hence stock prices forecasting very important in finance and business. For stockbrokers, understanding trends and supported by prediction software for forecasting is very important for decision making. This paper proposes a data science model...
Autor principal: | Budiharto, Widodo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948653/ https://www.ncbi.nlm.nih.gov/pubmed/33723498 http://dx.doi.org/10.1186/s40537-021-00430-0 |
Ejemplares similares
-
LSTM-based sentiment analysis for stock price forecast
por: Ko, Ching-Ru, et al.
Publicado: (2021) -
Forecasting of Covid-19 positive cases in Indonesia using long short-term memory (LSTM)
por: Sunjaya, Bryan Alfason, et al.
Publicado: (2023) -
Forecasting stock prices with long-short term memory neural network based on attention mechanism
por: Qiu, Jiayu, et al.
Publicado: (2020) -
An adaptive particle swarm optimization-based hybrid long short-term memory model for stock price time series forecasting
por: Kumar, Gourav, et al.
Publicado: (2022) -
Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data
por: Kim, Taewook, et al.
Publicado: (2019)