3 papers in the archive (2023–2024), average empirical rigor 4.7/10, average math complexity 6.8/10. Quadrant mix: Holy Grail ×2, Lab Rats ×1.
Works mostly in Factor Investing & Asset Pricing, Market Microstructure, Options & Derivatives Pricing.
Frequent co-authors: W. Brent Lindquist (3), Svetlozar T. Rachev (3), Davide Lauria (2), Frank J. Fabozzi (2), JiHo Park (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 address the problem of asset pricing in a market where there is no risky asset. Previous work developed a theoretical model for a shadow riskless rate (SRR) for such a market in terms of the drift component of the state-price deflator for that asset universe. Assuming asset prices are modeled by
Motivated by the Corns-Satchell, continuous time, option pricing model, we develop a binary tree pricing model with underlying asset price dynamics following Itô-Mckean skew Brownian motion. While the Corns-Satchell market model is incomplete, our discrete time market model is defined in the natural
We introduce a discrete binary tree for pricing contingent claims with the underlying security prices exhibiting history dependence characteristic of that induced by market microstructure phenomena. Example dependencies considered include moving average or autoregressive behavior. Our model is marke