Backtesting Software Development with Realistic Simulation
We build custom backtesters with tick/bar modes, slippage models, partial fills, funding, and corporate actions—so promotion to paper trading is a validation step, not a leap of faith.
Most backtests lie politely
Look-ahead bias, survivorship-free data, zero-cost fills, and optimized parameters on the same slice produce curves that live trading shatters.
- ×Bar-based tests intrabar paths unknowable—false precision.
- ×Crypto backtests ignore funding and fee tiers.
- ×FX ignores rollover and session spread widening.
- ×No walk-forward framework—just one glistening equity line.
Custom backtesting software with explicit assumptions
Documented fill models, point-in-time datasets, and parity hooks exporting same signals live system will consume.
- Tick and event-driven modes where data supports it.
- Parameter sweeps with walk-forward and holdout reporting.
- Cost models: spread, commission, slippage, funding, borrow.
- Export signals to production format for parity tests.
Teams serious about research governance
Funds and traders who need backtests as decision tools—not marketing charts.
Quant funds
Multi-asset backtester integrated with data lake.
Crypto systematic traders
Funding-aware perp simulation.
FX EA developers
MT5-aligned tick tests with broker spread profiles.
Fintech strategy marketplaces
Verified backtests for listed strategies.
Real-world delivery examples
Crypto perp backtester
Fund needed funding and tiered fee model on 3 years tick data.
Live paper drift under 5% vs sim on 90-day validation.
Prop EA verification reports
Vendor needed PDF backtests with spread stress scenarios for marketing.
Automated report gen cut manual Excel work from 4h to 12m per EA.
What you get
Configurable fill models
Market, limit, queue position, and partial fill logic.
Walk-forward engine
Rolling train/test windows with aggregated metrics.
Monte Carlo modules
Shuffle returns or resample trades for DD distributions.
Data quality checks
Gap detection, outlier flags, and survivorship notes.
Report generator
HTML/PDF with metrics table, DD chart, and assumptions appendix.
Live parity export
Same signal JSON production consumes for diff tests.
Technology stack
| Technology | Role in your build |
|---|---|
| Python / C++ | Simulation core for speed and flexibility |
| Pandas / Polars | Vectorized bar engines |
| Parquet / Arctic | Historical data storage |
| DuckDB | Ad hoc research queries on tick archives |
| Plotly / Matplotlib | Report visualizations |
Development process
- 01
Assumption workshop
Asset class, bar/tick, costs, and data sources.
- 02
Data pipeline
Ingest, clean, point-in-time store.
- 03
Engine MVP
Single strategy path with reports.
- 04
Parity hook
Export format matched to live runner.
- 05
Validation study
Compare paper vs backtest on holdout period.
Frequently asked questions
Build vs QuantConnect/Amibroker?+
Custom when you need parity with proprietary live stack or non-standard assets.
Tick data included?+
We integrate your vendors or recommend sources; licensing is client responsibility.
GPU acceleration?+
Available for massive parameter sweeps when justified.
Can you backtest MT5 EAs?+
Yes—align tester settings or external tick replay with same logic.
Machine learning backtests?+
Walk-forward and purged cross-validation supported.
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