3 papers in the archive (2025–2026), average empirical rigor 5.3/10, average math complexity 4.7/10. Quadrant mix: Holy Grail ×1, Philosophers ×1, Street Traders ×1.
Works mostly in Crypto Markets & DeFi, Market Microstructure, Stochastic Control & Optimal Stopping, Market Simulation & Agent-Based Models.
Frequent co-authors: Rem Sadykhov (2), Geoff Goodell (2), Konark Jain (1), Nick Firoozye (1), Jonathan Kochems (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 study the optimal Market Making problem in a Limit Order Book (LOB) market simulated using a high-fidelity, mutually exciting Hawkes process. Departing from traditional Brownian-driven mid-price models, our setup captures key microstructural properties such as queue dynamics, inter-arrival cluste
In this paper, we analyse the impacts of exogenous and endogenous factors on wealth distribution in the Bitcoin token economy, where wealth distribution refers to the distribution of BTC between economic participants or groups of economic participants. The objective of the paper is to analyse the im
This paper proposes a framework for categorizing economic policies in a form of a tree taxonomy. The purpose of this approach is to construct an exhaustive and standardized list of actions that a governing authority has access to and can change to control an economy. This is advantageous from two pe