4 papers in the archive (2022–2025), average empirical rigor 4.8/10, average math complexity 4.2/10. Quadrant mix: Lab Rats ×1, Street Traders ×3.
Works mostly in Fixed Income & Interest Rates, Risk Management & Tail Risk, NLP & LLMs in Finance, Machine Learning for Market Forecasting.
Frequent co-authors: Yan Zhang (3), Yixiang Tian (3), Xun Yu Zhou (1), Qi Wang (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
One type of bond with the most implicit government guarantee is municipal investment bonds. In recent years, there have been an increasing number of downgrades in the credit ratings of municipal bonds, which has led some people to question whether the implicit government guarantee may affect the obj
We study a continuous-time Markowitz mean-variance portfolio selection model in which a naive agent, unaware of the underlying time-inconsistency, continuously reoptimizes over time. We define the resulting naive policies through the limit of discretely naive policies that are committed only in very
Interpretability analysis methods for artificial intelligence models, such as LIME and SHAP, are widely used, though they primarily serve as post-model for analyzing model outputs. While it is commonly believed that the transparency and interpretability of AI models diminish as their complexity incr
The implicit government guarantee hampers the recognition and management of risks by all stakeholders in the bond market, and it has led to excessive debt for local governments or state-owned enterprises. To prevent the risk of local government debt defaults and reduce investors’ expectations of imp