4 papers
Time-Varying Factor-Augmented Models for Volatility Forecasting
Duo Zhang, Jiayu Li, Junyi Mo +1
Accurate volatility forecasts are vital in modern finance for risk management, portfolio allocation, and strategic decision-making. However, existing methods face key limitations.…
ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation
Junyi Mo, Jiayu Li, Duo Zhang +1
Missing data in financial panels presents a critical obstacle, undermining asset-pricing models and reducing the effectiveness of investment strategies. Such panels are often inher…
LinguaSynth: Heterogeneous Linguistic Signals for News Classification
Duo Zhang, Junyi Mo
Deep learning has significantly advanced NLP, but its reliance on large black-box models introduces critical interpretability and computational efficiency concerns. This paper prop…
Tensor-Fused Multi-View Graph Contrastive Learning
Yujia Wu, Junyi Mo, Elynn Chen +1
Graph contrastive learning (GCL) has emerged as a promising approach to enhance graph neural networks' (GNNs) ability to learn rich representations from unlabeled graph-structured…