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Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| infer relations from market signals rather than use predefined relations (ablation) | AD-GAT with the AM aggregator · S&P 500 | DA: 0.5501 -> 0.5647 | Helped |
| infer relations from market signals rather than use predefined relations (ablation) | AD-GAT with the AM aggregator · S&P 500 | AUC: 0.5550 -> 0.5894 | Helped |
| add the attribute-mattered aggregator instead of the linear aggregator (ablation) | AD-GAT with inferred relations · S&P 500 | DA: 0.5436 -> 0.5647 | Helped |
| add the attribute-mattered aggregator instead of the linear aggregator (ablation) | AD-GAT with inferred relations · S&P 500 | AUC: 0.5672 -> 0.5894 | Helped |
| use firm-specific tensor fusion instead of concatenating numerical and textual features (ablation) | AD-GAT · S&P 500 | DA: 0.5450 -> 0.5647 | Helped |
| use firm-specific tensor fusion instead of concatenating numerical and textual features (ablation) | AD-GAT · S&P 500 | AUC: 0.5604 -> 0.5894 | Helped |
| use firm-specific rather than shared tensor fusion (ablation) | AD-GAT · S&P 500 | DA: 0.5542 -> 0.5647 | Helped |
| use firm-specific rather than shared tensor fusion (ablation) | AD-GAT · S&P 500 | AUC: 0.5679 -> 0.5894 | Helped |
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