Quantitative stock portfolio optimization by multi-task learning risk and return
Selecting profitable stocks for investments is a challenging task. Recent research has made
significant progress on stock ranking prediction to select top-ranked stocks for portfolio …
significant progress on stock ranking prediction to select top-ranked stocks for portfolio …
A dynamic attributes-driven graph attention network modeling on behavioral finance for stock prediction
Q Zhang, Y Zhang, X Yao, S Li, C Zhang… - ACM Transactions on …, 2023 - dl.acm.org
Stock prediction is a challenging task due to multiple influencing factors and complex market
dependencies. Traditional solutions are based on a single type of information. With the …
dependencies. Traditional solutions are based on a single type of information. With the …
A multiscale time-series decomposition learning for crude oil price forecasting
J Tan, Z Li, C Zhang, L Shi, Y Jiang - Energy Economics, 2024 - Elsevier
Crude oil price forecasting is important for market participants and policymakers. However,
accurately tracking oil prices is quite a challenging task due to the complexity of temporal oil …
accurately tracking oil prices is quite a challenging task due to the complexity of temporal oil …
Towards human-like perception: Learning structural causal model in heterogeneous graph
Heterogeneous graph neural networks have become popular in various domains. However,
their generalizability and interpretability are limited due to the discrepancy between their …
their generalizability and interpretability are limited due to the discrepancy between their …
Graph learning and its advancements on large language models: A holistic survey
Graph learning is a prevalent domain that endeavors to learn the intricate relationships
among nodes and the topological structure of graphs. Over the years, graph learning has …
among nodes and the topological structure of graphs. Over the years, graph learning has …
MRRFGNN: Multi-relation reconstruction and fusion graph neural network for stock crash prediction
J Wang, L Liao, K Zhong, M Deveci, P du Jardin… - Information …, 2025 - Elsevier
Stock crash risk often propagates through various interconnected relationships between
firms, amplifying its impact across financial markets. Few studies predicted the crash risk of …
firms, amplifying its impact across financial markets. Few studies predicted the crash risk of …
Cross-modal scenario generation for stock price forecasting using Wasserstein GAN and GCN
Z Wang, B Wang, Y Li, S Liu, H Li, J Watada - Applied Soft Computing, 2024 - Elsevier
The forecasting of stock price has always been a difficult problem, as the various inputs like
company performance, technical innovation, political factors are intricate and often assessed …
company performance, technical innovation, political factors are intricate and often assessed …
FedLive: A federated transmission framework for panoramic livecast with reinforced variational inference
Providing premium panoramic livecast services to worldwide viewers considering their ultra-
high data rate and delay-sensitivity is a significant challenge in the current network delivery …
high data rate and delay-sensitivity is a significant challenge in the current network delivery …
ESIE-BERT: Enriching sub-words information explicitly with BERT for intent classification and slot filling
Natural language understanding (NLU) has two core tasks: intent classification and slot
filling. The success of pre-training language models resulted in a significant breakthrough in …
filling. The success of pre-training language models resulted in a significant breakthrough in …
A Graph-Based Network with Attention for Stock Price Prediction
H Fu - 2023 International Conference on Communications …, 2023 - ieeexplore.ieee.org
In today's world, graph-based data and models have become increasingly important and
indispensable. As a result of graph-based neural networks' excellent ability to process these …
indispensable. As a result of graph-based neural networks' excellent ability to process these …