Interpretable Stock Anomaly Detection Based on Spatio-Temporal Relation Networks With Genetic Algorithm
Instability in financial markets represents a considerable risk to investors; examples of instability include a market crash caused by systematic risks and abnormal stock price volatility caused by artificial hype. The early detection of abnormal behavior can help investors adjust their strategy and...
Main Authors: | Mei-See Cheong, Mei-Chen Wu, Szu-Hao Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9420709/ |
Similar Items
-
Spatio-Temporal Anomaly Detection
by: Das, Mahashweta
Published: (2009) -
Spatio-Temporal Unity Networking for Video Anomaly Detection
by: Yuanyuan Li, et al.
Published: (2019-01-01) -
Genetic Algorithm based feature selection and Naïve Bayes for anomaly detection in fog computing environment
by: John Oche Onah, et al.
Published: (2021-12-01) -
PRAAG Algorithm in Anomaly Detection
by: Zhang, Dongyang
Published: (2016) -
Design and Implementation of Parallel Anomaly Detection
by: Shanbhag, Shashank
Published: (2007)