STGAT: Spatial–Temporal Graph Attention Neural Network for Stock Prediction
Stock price prediction and portfolio optimization are critical research areas in financial markets, as they directly impact investment strategies and risk management. Traditional statistical methods and machine learning approaches have been widely applied to these tasks, but they often fail to fully...
Saved in:
| Main Authors: | Ruizhe Feng, Shanshan Jiang, Xingyu Liang, Min Xia |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/8/4315 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Effectiveness of Open, High and Low Prices in Stock Market Price Prediction
by: Collins C. Ngwakwe
Published: (2025-03-01) -
Multi-Cluster Graph (MCG): A Novel Clustering-Based Multi-Relation Graph Neural Networks for Stock Price Forecasting
by: Yasmeen Ansari
Published: (2024-01-01) -
A Dual Output Temporal Convolutional Network With Attention Architecture for Stock Price Prediction and Risk Assessment
by: Arindam Kishor Biswas, et al.
Published: (2025-01-01) -
Is the influence of oil prices changes on oil and gas stock prices in Nigeria symmetric or asymmetric?
by: Dasauki Musa, et al.
Published: (2022-12-01) -
CIRGNN: Leveraging Cross-Chart Relationships with a Graph Neural Network for Stock Price Prediction
by: Shanghui Jia, et al.
Published: (2025-07-01)