We help hedge funds create more alpha.
TL:DR; We figured out how to fit custom equity factor risk models in seconds instead of weeks. And we can do this across the entire financial analytics landscape. Ad hoc thematic factor construction (think COVID), risk decomposition through time, optimized factor selection, all on the fly and in seconds.
Try out our demo here.
We each spent nearly a decade at BlackRock and Bloomberg, building products, leading research teams, and empathizing with frustrated clients. They sit at the cutting edge of investment research, coming up with market-beating strategies. Yet they have to make do with a 20-year-old analytics toolkit that current vendors offer.
We are changing that. If the AI community can fit a 300 billion parameter model, there’s no reason why a factor risk model should take a week to compute. In fact, it doesn’t. We figured out how to do it live and in seconds, and we can do it across the entire analytics landscape.
Hi, we’re Sebastian and Misha.
Sebastian, CFA built his expertise in quant research during his time as a Director in BlackRock’s Financial Modeling Group where he implemented and researched equity risk models that analyze trillions in assets.
Prior to Bayesline, he was at Bloomberg, where he incubated the next generation of customizable and actionable quant products as part of the Quant & AI Research group.
A computer scientist by training with M.Sc. in Finance and a passion for quant research, Sebastian spent the last 10 years leveraging the power of machine learning to challenge, innovate, and reshape how institutions think about financial modeling.
Misha, PhD was among the youngest Managing Directors at BlackRock. He headed the portfolio risk research team that evolved Aladdin’s portfolio risk models across all asset classes.
He also headed the team that developed Aladdin’s economic scenario engine and investment models that manage roughly $400 billion in strategic asset allocations.
Misha has spent the past 10 years coupling his professional quant training with his personal interest in all things AI and hands-on engineering.