3 papers in the archive (2024–2026), average empirical rigor 5.3/10, average math complexity 7.7/10. Quadrant mix: Holy Grail ×2, Lab Rats ×1.
Works mostly in Market Microstructure, Stochastic Control & Optimal Stopping, Options & Derivatives Pricing, Risk Management & Tail Risk.
Frequent co-authors: Arnab Kumar Laha (1), Priyanshu Tiwari (1), Dhruv Bansal (1), Mayank Goud (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%).
In the Vasicek credit portfolio model, tail risk is driven primarily by the asset-correlation parameter, yet empirically is subject to correlation risk. We propose a stochastic correlation extension of the Vasicek framework in which the correlation state evolves as a diffusion on the circle. This re
We develop diffusion models for time-varying correlation using stochastic processes defined on the unit circle. Specifically, we study Brownian motion on the circle and the von Mises diffusion, and propose their use as continuous-time models for correlation dynamics. The von Mises process, introduce
We develop a tractable framework for valuing Asian options when trading the underlying generates market impact and execution costs. Starting from a discrete-time, quote-level model, we construct a reference midpoint suitable for Asian payoffs and separate market impact into a transient component and