We operate from a core belief: that even the most-watched public stock markets are not perfectly efficient. Our purpose is to systematically identify and exploit these structural inefficiencies.

To do this, we develop proprietary, algorithm-driven strategies focused on mid- to mega-cap equities. Each strategy is a unique blend of nonlinear modeling and disciplined risk management, and in a nod to our name, each is titled after a famous work of art.

Our process is centered on a proprietary algorithm designed to identify structural market inefficiencies that skew future returns. We deploy an ensemble of strategies that operate on both daily and weekly cadences, executing trades at predetermined times. This systematic approach is best described as a medium-frequency skewness arbitrage strategy, focused on capturing alpha in mid-, large-, and mega-cap stocks. 

Our algorithms are designed to assist inference in complex adaptive systems (CAS). This is achieved through dimension reduction procedures and preservation of ergodicity using inputs from real-world CAS. The market provides a robust environment to test the predictability of realtime emergent asymmetries and performance suggests the ability to earn returns unavailable to traditional strategies (by MPT assumptions).