4 papers in the archive (2023), average empirical rigor 5.1/10, average math complexity 6.5/10. Quadrant mix: Holy Grail ×1, Lab Rats ×2, Street Traders ×1.
Works mostly in Options & Derivatives Pricing, Volatility Modeling & Forecasting, Fixed Income & Interest Rates.
Frequent co-authors: Jeonggyu Huh (1), Nan Su (1), Yue Kuen Kwok (1), Lan Ju (1), Jian Li (1), Zhiyong Tu (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%).
Exact simulation schemes under the Heston stochastic volatility model (e.g., Broadie-Kaya and Glasserman-Kim) suffer from computationally expensive modified Bessel function evaluations. We propose a new exact simulation scheme without the modified Bessel function, based on the observation that the c
Traditional art pricing models often lack fine measurements of painting content. This paper proposes a new content measurement: the Shannon information quantity measured by the singular value decomposition (SVD) entropy of the painting image. Using a large sample of artworks’ auction records and ima
The stochastic-alpha-beta-rho (SABR) model has been widely adopted in options trading. In particular, the normal ($β=0$) SABR model is a popular model choice for interest rates because it allows negative asset values. The option price and delta under the SABR model are typically obtained via asympto
Using the option delta systematically, we derive tighter lower and upper bounds of the Black-Scholes implied volatility than those in Tehranchi [SIAM J. Financ. Math. 7 (2016), 893-916]. As an application, we propose a Newton-Raphson algorithm on the log price that converges rapidly for all price ra