Identifying and Forecasting Recurrently Emerging Stock Trend Structures via Rising Visibility Graphs
This study introduces a novel forecasting framework that identifies and predicts recurrently emerging structural patterns in stock trends using rising visibility graphs (RVGs) and the Weisfeiler–Lehman (WL) subtree kernel. The proposed method, RVGWL, addresses a key limitation of traditional visibil...
Saved in:
| Main Authors: | Zhen Zeng, Yu Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Forecasting |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-9394/7/2/26 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Microgrid Multivariate Load Forecasting Based on Weighted Visibility Graph: A Regional Airport Case Study
by: Georgios Vontzos, et al.
Published: (2025-04-01) -
A model based LSTM and graph convolutional network for stock trend prediction
by: Xiangdong Ran, et al.
Published: (2024-09-01) -
Enhanced visibility graph for EEG classification
by: Asma Belhadi, et al.
Published: (2025-05-01) -
Time Series Forecasting Based on Temporal Networks Evolution and Dynamic Constraints
by: Yunlong Peng, et al.
Published: (2025-01-01) -
Enhanced Radar Signal Classification Using AMP and Visibility Graph for Multi-Signal Environments
by: Ji-Hyeon Kim, et al.
Published: (2024-11-01)