3 papers in the archive (2025–2026), average empirical rigor 7.7/10, average math complexity 4.5/10. Quadrant mix: Holy Grail ×2, Street Traders ×1.
Works mostly in Crypto Markets & DeFi, Fixed Income & Interest Rates.
Frequent co-authors: Junliang Luo (2), Katrin Tinn (2), Yupeng Cao (1), Xueqing Peng (1), Lingfei Qian (1), Haohang Li (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%).
Language agents increasingly work for users on the open Web, and finance is where trusting them is hardest. The data must come from the Web, the strategy lives in the user’s head, and correctness depends on time, so an agent can fail silently: a strategy the user never asked for, unverified data, or
Tokenized U.S. Treasuries have emerged as a prominent subclass of real-world assets (RWAs), offering cryptographically enforced, yield-bearing instruments collateralized by sovereign debt and deployed across multiple blockchain networks. While the market has expanded rapidly, empirical analyses of t
The global financial architecture is undergoing a shift from intermediary centric-settlement to programmable infrastructure, to transmute trillions in static illiquid capital into active, high-velocity instruments. We argue that Real World Asset (RWA) tokenization represents a conceptual evolution b