Neuronomics’ unique approach allows for the real-time identification of unexplored market inefficiencies that arise repeatedly due to the evolutionary-biased processing or financial information in the human brain. To identify the neuronal-processing-induced market inefficiencies, we combine approaches from quantitative finance with research insights from computational neuroscience regarding the neuronal processing of financial uncertainties, gains and losses.
Identifying such patterns based on neuroscientific research allows us to exploit short-term market opportunities without running into over-fitting and generalizing problems that often negatively affect pure quantitative approaches. On this basis, Neuronomics develops quantitative algorithms that generate systematic alpha uncorrelated to traditional markets and investment strategies. The neuronal processing of market participants exhibits similar traits across all asset classes, enabling Neuronomics to generate uncorrelated returns from multiple asset classes.