Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda
The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing neural a...
Guardado en:
Autores principales: | Ritika Chopra, Gagan Deep Sharma |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/1d24f554e2584bd4a02e7a6d29f9dd19 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Forecasting stock returns on the Amman Stock Exchange: Do neural networks outperform linear regressions?
por: Abdel Razzaq Al Rababa’a, et al.
Publicado: (2021) -
How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature
por: Azra Zaimovic, et al.
Publicado: (2021) -
External Shocks and Volatility Overflow among the Exchange Rate of the Yen, Nikkei, TOPIX and Sectoral Stock Indices
por: Mirzosaid Sultonov
Publicado: (2021) -
Impact of COVID-19 on the Stock Market by Industrial Sector in Chile: An Adverse Overreaction
por: Pedro Antonio González, et al.
Publicado: (2021) -
Idiosyncratic volatility, investor sentiment, and returns of the GCC stock markets
por: Shah Saeed Hassan Chowdhury
Publicado: (2021)