collaborators

5 papers

cs.LG2026

Interpretable Factor Decomposition for Decision Intelligence in Large-Scale Financial Markets: Evidence from China's A-Share Market

Xiao Han, Yao Xiao, Zhen Zhang +1

We present an interpretable machine learning pipeline to decompose cross-sectional equity return predictability into auditable factor contributions. We apply an XGBoost model with…

cs.LG2026

Interpretable vs Learned Encoders for High-Cardinality Fraud Detection

Xiao Han, Jingjing Liu, Moxuan Zheng +2

A total of seven categorical encoding methods were tested on the IEEE-CIS fraud benchmark dataset (590,540 records, 3.5% positives, 8 high-cardinality columns). The encoders were e…

q-fin.RM2026

Bankruptcy Prediction from 10-K Narratives: Evidence from Interpretable Text Scores and Accounting Baselines

Zhen Zhang, Moxuan Zheng, Tongchen Zhang +3

Bankruptcy is a low-frequency but high-impact corporate event, making early risk identification important for creditors, investors, regulators, and risk managers. Traditional bankr…

cs.CR2026

Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection

Lixing Lin, Juli You, Yue Li +4

Large language model (LLM) safety classifiers such as Llama Guard are effective at detecting overtly harmful prompts but remain vulnerable to adversarial jailbreak attacks that dis…

q-fin.TR2026

A Volume-Price-Adjusted MACD Trading Strategy with Sensitivity Calibration for U.S. Equity Indices

Luyun Lin, Lixing Lin, Zhen Zhang +2

Traditional moving average convergence divergence (MACD) trading rules are often constrained by signal lag and susceptibility to false signals. To address these limitations, this s…