Markets are systems.
We study the system.
DaraHoosh is a quantitative research and financial technology institution — mathematics, engineering and capital, operated as one continuous system.
We treat markets as a large, partially observable system — and build the mathematics, software and infrastructure needed to study it rigorously.
That means research culture over conviction, engineering discipline over speed for its own sake, and a hiring bar set by the hardest problems we work on — not by headcount targets.
Research first
Every strategy begins as a hypothesis, tested with the same statistical discipline a physics lab would apply to a new result.
Engineering as method
Infrastructure is not support staff for research — it is where research becomes reproducible, auditable and fast to iterate on.
Selective by design
Scale is a consequence of being right often enough, not a goal in itself. We stay small enough to move like a research group.
A research culture with a physics lab’s standard of evidence.
Quantitative Research
Systematic investigation of market structure, price formation and the statistical properties of financial time series.
Machine Learning
Learned representations of noisy, non-stationary data, evaluated with the same statistical rigor as any classical model.
Statistical Modeling
Estimation, inference and model validation under regime change, fat tails and limited sample sizes.
Market Microstructure
How order flow, liquidity provision and venue mechanics shape price at the smallest observable timescales.
Optimization
Portfolio and execution problems formulated and solved under real-world constraints, not idealized ones.
Alternative Data
Extracting signal from unconventional data sources while holding a high bar for statistical significance.
Simulation
Market and agent-based simulation used to stress-test models before capital ever touches them.
Applied Mathematics
Stochastic processes, functional analysis and numerical methods as working tools, not abstractions.
Infrastructure built to the same standard as the research it carries.
Distributed systems, low-latency execution and research tooling engineered by people who also use them daily — not a separate platform team working from a spec.
Technology at DaraHooshDistributed Systems
Research and execution platforms built to stay correct under partial failure, not just under normal operation.
Low-Latency Infrastructure
Network, hardware and software co-designed so the path from signal to order stays measured, not assumed.
Compute
Research compute sized for iteration speed — the constraint that most determines how fast ideas get tested.
Data Engineering
Pipelines that treat data lineage, point-in-time correctness and reproducibility as non-negotiable.
ML Infrastructure
Training and evaluation infrastructure built around rigorous backtesting discipline, not just throughput.
Research Tooling
Internal tools that let a researcher move from hypothesis to evidence in hours, not weeks.
Execution Systems
Order and execution management engineered for determinism, auditability and graceful degradation.
Observability & Reliability
Systems instrumented so that anomalies are caught by monitoring, not by a research desk noticing P&L drift.
Strategy families, described at an institutional level.
Systematic Strategies
Rules-derived positioning built from tested signals rather than discretionary judgment.
Quantitative Equities
Cross-sectional and statistical approaches to equity markets, grounded in factor and microstructure research.
Macro
Systematic interpretation of macroeconomic and cross-asset regime signals.
Relative Value
Pricing relationships across related instruments, isolated from broad market direction.
Execution
Translating a decision into a fill with minimal market impact and full auditability.
Portfolio Construction
Combining independent signals into a single portfolio under explicit risk constraints.
Infrastructure, extended.
Platforms built to run our own research and execution are, in places, made available to institutional counterparties — distinct from any investment activity described above.
Institutional Software
Internal platforms extended to institutional counterparties.
Execution Technology
Order routing, execution analytics and transaction cost measurement.
Analytics
Portfolio and risk analytics built on the same infrastructure as internal research.
Data Systems
Market and reference data infrastructure engineered for correctness under scale.
APIs
Programmatic interfaces to trading, data and analytics infrastructure.
Risk Technology
Real-time exposure, limit and scenario systems.
Selected numerical facts
Figures on this page are structural placeholders pending verification and are not to be relied upon. See disclosures.
Writing from the research floor.
A constellation of disciplines — mathematics, physics, computer science and market practice — working from a shared standard of evidence.
We hire for depth in a discipline and curiosity outside it. Researchers ship code; engineers read the research they support. The distance between an idea and its test is deliberately short.
We are competing for people who could work anywhere, and choose to work on the hardest problems.
Intelligence in motion. Engineering in service of conviction.