4 papers in the archive (2023–2025), average empirical rigor 4.8/10, average math complexity 7.5/10. Quadrant mix: Holy Grail ×2, Lab Rats ×2.
Works mostly in Options & Derivatives Pricing, Factor Investing & Asset Pricing, Volatility Modeling & Forecasting, Risk Management & Tail Risk.
Frequent co-authors: Svetlozar T. Rachev (3), W. Brent Lindquist (2), Nancy Asare Nyarko (1), Bhathiya Divelgama (1), Blessing Omotade (1), Svetlozar Rachev (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%).
We explore credit risk pricing by modeling equity as a call option and debt as the difference between the firm’s asset value and a put option, following the structural framework of the Merton model. Our approach proceeds in two stages: first, we calibrate the asset volatility using the Black-Scholes
We introduce a fairly general, recombining trinomial tree model in the natural world. Market-completeness is ensured by considering a market consisting of two risky assets, a riskless asset, and a European option. The two risky assets consist of a stock and a perpetual derivative of that stock. The
We present a unified, market-complete model that integrates both the Bachelier and Black-Scholes-Merton frameworks for asset pricing. The model allows for the study, within a unified framework, of asset pricing in a natural world that experiences the possibility of negative security prices or riskle
This paper delves into the dynamics of asset pricing within Bachelier market model, elucidating the representation of risky asset price dynamics and the definition of riskless assets.