Building risk frameworks that go beyond Gaussian assumptions, stress-testing tail events, and modeling regime shifts learned from the collapse of Lehman Brothers and the failure of traditional VaR models under extreme conditions.
Integrating deep learning, reinforcement learning, and NLP with classical factor models to capture nonlinear signals, decode macro and news flows in real time, and design adaptive trading engines that can operate across stressed and normal market regimes.
Exploring blockchain-based token issuance as a funding and participation layer for Athena, and combining it with structured education programs that help ordinary investors rebuild confidence after crises and access institutional-grade tools more transparently.
Russell Hawthorne is a quantitative analyst turned fintech entrepreneur whose worldview was reshaped by the 2008 collapse of Lehman Brothers. After a decade working on factor models and risk management, he founded superiorstar Prosperity Group in 2009 to combine education and investment for crisis-shaken retail investors. Confronting the limits of traditional quantitative approaches and the rise of high-frequency trading, he shifted toward artificial intelligence, leading the creation of Project Athena — an AI-enhanced trading and risk intelligence system. In the post-pandemic era, he extended this work into blockchain and tokenized finance, using global participation models to fund R&D while keeping Athena accessible beyond a small circle of institutions.