Reported alpha from end-to-end LLM trading agents does not constitute deployment evidence until it passes structural tests for temporal integrity, frictions, robustness, calibration, execution, and disaggregation.
Empirical asset pricing via machine learning.The Review of Financial Studies, 33(5):2223–2273, 2020
2 Pith papers cite this work. Polarity classification is still indexing.
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A TCN plus Attention-LSTM model trained on 2014-2024 Chinese A-share data outperforms static baselines and identifies prolonged undervaluation as the long-term driver and sudden cash-flow increases as the short-term trigger for repurchases.
citing papers explorer
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The Alpha Illusion: Reported Alpha from LLM Trading Agents Should Not Be Treated as Deployment Evidence
Reported alpha from end-to-end LLM trading agents does not constitute deployment evidence until it passes structural tests for temporal integrity, frictions, robustness, calibration, execution, and disaggregation.
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Dynamic Forecasting and Temporal Feature Evolution of Stock Repurchases in Listed Companies Using Attention-Based Deep Temporal Networks
A TCN plus Attention-LSTM model trained on 2014-2024 Chinese A-share data outperforms static baselines and identifies prolonged undervaluation as the long-term driver and sudden cash-flow increases as the short-term trigger for repurchases.