One quantitative fund. Research is read from more than one angle. The book is built to be market-neutral, sector-neutral, and factor-neutral.
The fundamental layer sits inside the same quantitative book.
Filings, customers, and suppliers are read by the system.
Primary research involving customers, competitors, and supply chains.
Healthcare, TMT, Consumer, Industrials, and FinTech specialization.
Our systematic business operates at the intersection of data science and finance. We view the market as a noisy dataset where subtle signals—imperceptible to the human eye—can be extracted using advanced statistics.
Machine learning adapts the book to changing market regimes. The process is automated, disciplined, and scalable.
Ingesting alternative data (satellite, weather, credit) to forecast price movements.
Factor exposure stays inside the limits.
Early-stage companies are research subjects for the book.
The system reads how they use AI, machine learning, and advanced computing.
How early-stage companies build with AI, machine learning, and advanced computing.
How those companies show up in the industries the book covers.
Mature businesses in technology and data are research subjects for the same book.
The system reads how those businesses operate.
How established businesses in technology and data are built.
How those businesses run their systems.
Alpha generation is impossible without capital preservation. Our independent Risk Management team has the authority to reduce positions or shut down trading strategies that exceed defined limits.
Positions are monitored continuously. Breaches trigger automated reduction protocols.
Portfolios are subjected to historical crisis scenarios (2008, 2020) daily.
We ensure that our 'diversified' bets are not secretly correlated to a single factor.