The range of work the firm takes on.
What follows is the scope of research and engineering engagements accepted: the markets, instruments and methods the firm builds against on behalf of clients.
It is not a description of markets the firm trades. Hessian Research does not trade proprietary capital and does not manage client money.
Global
Any market where data can be obtained, research can be done and orders can be routed. Venue and jurisdiction are engineering constraints (data availability, market structure, session times, clearing and connectivity), not a limit on what work is accepted.
In practice a mandate is scoped to the venues a client already trades. The relevant question is whether the data and the execution path exist, not where they are.
Cross-asset
Vanilla through to complex, listed and over the counter.
Non-linear instruments are where the method in Method stops being decorative. A payoff whose value depends on the path, or on more than one underlying, has second-order structure that a first-order risk view does not capture, and that structure is where multi-asset books tend to fail.
Across the frequency spectrum
From low-frequency systematic through intraday to latency-sensitive execution.
- Systematic & relative value
- Signal research, portfolio construction and risk models for holding periods measured in days to months. Statistical arbitrage and relative value across instruments and venues.
- Volatility & derivatives
- Surface construction and fitting, pricing and calibration, second-order risk on books with more than one underlying, and the hedging logic that follows from it.
- Market structure
- Microstructure research, execution quality measurement, and latency-sensitive order routing. This is execution engineering rather than latency arbitrage: the firm builds routing and measurement; it does not operate a colocated trading business.
What is actually applied
Machine learning is applied where the structure of the problem justifies it, which on financial data is less often than the literature suggests. Where a regularised linear model and an honest evaluation scheme answer the question, that is what gets used.