3 papers in the archive (2023–2026), average empirical rigor 6.7/10, average math complexity 4.3/10. Quadrant mix: Holy Grail ×2, Street Traders ×1.
Works mostly in Crypto Markets & DeFi, Reinforcement Learning for Trading, Risk Management & Tail Risk, NLP & LLMs in Finance.
Frequent co-authors: Yebo Feng (3), Yichen Luo (2), Daniel Perez (1), Benjamin Livshits (1), Paolo Tasca (1), Yang Liu (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%).
Total value locked (TVL) is widely used to measure the size and popularity of decentralized finance (DeFi). However, TVL can be easily manipulated and inflated through “double counting” activities such as wrapping and leveraging. As existing methodologies addressing double counting are inconsistent
Decentralized finance (DeFi) is an integral component of the blockchain ecosystem, enabling a range of financial activities through smart-contract-based protocols. Traditional DeFi governance typically involves manual parameter adjustments by protocol teams or token holder votes, and is thus prone t
The launch of $Trump coin ignited a wave in meme coin investment. Copy trading, as a strategy-agnostic approach that eliminates the need for deep trading knowledge, quickly gains widespread popularity in the meme coin market. However, copy trading is not a guarantee of profitability due to the preva