What We Do

Oak St. is a global quantitative hedge‑fund employing mathematical, statistical, and computational methods across liquid financial markets. The firm was founded in Chicago to trade futures, equities, and currencies systematically, and it has built its research, its technology, and its approach to risk around that one discipline rather than around any single strategy.

Research, engineering, and trading sit together in one team. Ideas are written down, tested against data, and reviewed by people whose job is to find what is wrong with them before the market does.

Investment Management

We examine large and diverse datasets in search of persistent relationships across instruments, markets, and time horizons.

Individual effects may be modest. In aggregate, properly validated and diversified, they can become economically meaningful.

Approaches

We take a research- and data-driven approach to investing. Our strategies are systematic by construction, and the judgment of experienced people is applied at the level of the portfolio rather than trade by trade.

Systematic Strategies

Our systematic strategies rest on quantitative and computational methods developed through the firm's own research and trading. Signals are drawn from large and diverse datasets, validated out of sample, and combined by rules that are fixed before capital is committed. The aim is to find small, persistent effects that survive careful testing, and to hold enough of them that no single one matters much.

Portfolio Oversight

Models decide what to trade; people decide what the models are allowed to do. Portfolio managers set the risk budget for each strategy, review its behavior against what was expected of it, and step in when markets move outside the conditions a model was built for. That oversight draws on the same data and infrastructure as the research, so judgment and measurement are never far apart.

Capabilities

Our investment activity is organised into four broad categories:

  • Futures

    Systematic strategies in listed futures on equity indices, government bonds, short-term interest rates, currencies, and commodities, traded on regulated exchanges around the clock.

  • Equities

    Statistical strategies in liquid single-name stocks and exchange-traded funds, built from many small, diversified positions rather than a handful of concentrated ones.

  • Currencies

    Systematic trading in the major and the more liquid emerging-market currency pairs, where deep and continuous markets suit models that trade often and size carefully.

  • Cross-Asset

    Forecast-driven portfolios that combine the firm's signals across asset classes, allocating risk where the evidence is strongest and netting the exposures that offset one another.

Technology Development

Technology is not a support function at Oak St.; it is most of what the firm builds. Research, data, trading, and risk all run on systems designed in house by engineers who sit with the people who use them. Where a tool we could buy falls short of what the research demands, we write the tool.

The stack is deliberately plain: a governed data estate with point-in-time histories, a research platform that makes every experiment reproducible, and a trading path that is measured end to end. Engineers own their systems in production and answer for how they behave on the busiest days of the year.

The team building it is small and growing; the roles we are hiring for are listed under How To Join.

Open Source

Nearly everything we build stands on open source software: the scientific Python stack, columnar storage formats, the Linux kernel, and the network tooling around it. We think the fair response is to give back, in code, in review, and in money for the people who maintain what we depend on.

Our open source contributions to date include:

  • Upstream fixes and features to the scientific Python libraries our research runs on
  • Funding for the maintainers of the storage and time-series tooling we rely on
  • Internal libraries for point-in-time data access, released under permissive licences
  • Participation in open standards work on array and dataframe interoperability

More of our work is on GitHub.

Risk Management

Risk management at Oak St. is not a department that reviews the trading after the fact; it is built into how every strategy is designed, sized, and monitored. Our view is a simple one: over a long enough horizon, what a strategy returns matters less than whether it survives its worst month.

Every strategy runs inside limits that are set before it trades: on gross and net exposure, on concentration, on liquidity, and on the loss at which it is cut back. Those limits are enforced by the trading systems themselves rather than by convention, and everyone who runs a model is also its first risk manager.

Capital allocation and the firm's risk limits are set by a Risk Committee made up of:

  • The founding partners
  • The head of risk
  • The heads of research and trading

We write about how we think about drawdowns and diversification in our Library.

Spotlight: Entrepreneurship

Oak St. began as a small group with a research question and the conviction to build a firm around it. The same instinct, to make something where nothing suitable exists, still shapes how we work.

The firm's trading, data, and research platforms were built rather than bought, by a team that treats each system as a product with users to serve. Several of those systems have grown into capabilities of their own, and we expect some of them to outlive the purpose they were first written for.

We back that spirit inside the firm. Engineers and researchers are given the time and the budget to pursue ideas that do not yet have a business case, and the firm's founders remain its most demanding early users.

Industry Leadership

Our people take part in the exchange advisory groups and industry committees where market structure and operating standards are discussed, bringing the perspective of a firm that trades systematically across many venues.

We publish what we can about our methods, our infrastructure, and the lessons of managing portfolios through difficult markets, in the belief that a more transparent industry is a more durable one.