Independent research / In development
Research,
engineered.
Building the infrastructure behind disciplined quantitative research. From reliable market data to realistic simulation and risk-aware execution systems.
Engineering in public. Trading logic kept private.
01 / The infrastructure
A connected stack.
A deliberate process.
Good research needs more than a promising idea. It needs dependable inputs, reproducible experiments, and execution assumptions that hold up to scrutiny.
Trust the inputs
before the outputs.
Market-data ingestion, historical caching, time-series alignment, and data-quality checks form the foundation of reproducible research.
- API and streaming adapters
- Historical time-series caching
- Timestamp and coverage validation
02 / Our approach
Evidence first.
Execution later.
A backtest is a research instrument, not a promise. We focus on the work between an interesting hypothesis and a defensible deployment decision.
Read the project overview- 01
Make it reproducible.
Track research settings, preserve data provenance, and make experiments repeatable instead of relying on isolated results.
- 02
Model the friction.
Account for latency, transaction costs, slippage, and conservative fill assumptions. A clean chart is not the same as an executable trade.
- 03
Earn the next step.
Use chronological validation and execution safeguards. Research results are not automatically promoted into live trading.
03 / The venture
An independent venture.
An engineering mindset.
QuantStacks is a quantitative research and trading-technology venture in development. The project brings together software engineering, market-data infrastructure, realistic simulation, and risk-aware system design.
We share the architecture and the standards behind the work. Proprietary signals, thresholds, and trading rules remain private.
THE WORK IS IN THE STACK.