Meet PSIMON:
Your AI SuperAnalyst
A groundbreaking platform boasting adaptability, resilience and institutional-grade AI, based on years of partnering with leading academic researchers.
Machine Learning & AI is changing the game for the world’s largest asset managers, who are investing at breakneck speed, building teams of data scientists, and supporting them with software engineers and massive computing power. But what many are discovering is that building predictive portfolio AI is no easy task.
With Portfolio AI, good isn't good enough
PSIMON was designed from the ground up to recognize regime change and structural breaks; to adapt when markets are in flux. It has been trained on an extensive library of over 100,000 historical financial events. Moreover, its flexible design means that it can be quickly trained on new data streams, for new models and strategies.
Multiple Forecasters
PSIMON generates multiple high quality forecasts using different types of analysis — studying technicals and fundamentals alongside macro economic data, debt and credit cycles, behavioral and momentum analysis and more.
Rating Probabilities with MetaLearning
PSIMON isn’t tied to any one investment philosophy or analytic strategy; with each computational pass, its metalearner module compares multiple forecasts, deciding which ones are most likely in the current environment.
Analysis, AI and Allocation
PSIMON’s number crunching — across a wide range of data-types and analyses — builds a predictive map for each strategy, across a chosen time window, and for a chosen risk profile.
Resilience in Black Swan Scenarios
PSIMON is quick-witted and uniquely able to adapt in seemingly unpredictable times. Trained on data spanning major market crashes and financial shocks, we have used some of the strictest proprietary stress- and back-testing techniques to ensure PSIMON can perform under pressure, including extreme corner cases, both slow and sudden. Moreover, we are continually introducing new “test vectors” so that PSIMON grows more robust with each passing month.
