Simulations that delivers predictable results
Validating trading strategies requires accurate historical data that mirrors real-world market conditions.
The quality of backtests directly depends on the completeness, accuracy, and granularity of market data. Simulations based on filtered or low-resolution data can produce misleading results, wasted capital, and failed strategies. FinFeedAPI delivers raw, unfiltered market messages, including order book activity, auction pricing, trade executions, and admin events, enabling developers and quants to build high-fidelity strategy simulations that reflect real market behavior, not idealized conditions.
Developer challenges:
Filtered or incomplete historical data distorts test results
Lack of granular timestamps limits precision in simulation
Inability to model order-level behavior and queue dynamics
Missed edge-case events like halts, IPOs, or split adjustments
Complexity of merging data from different event feeds
Poor metadata alignment across backtesting environments
What You Can Achieve with FinFeedAPI
Run High-Fidelity Simulations with Nanosecond Precision
- Timestamped at nanosecond level for exact sequencing of market events.
- Eliminate the guesswork when simulating latency, slippage, and queue placement.
- Ideal for testing high-frequency, event-driven, or latency-sensitive strategies.
Simulate with Unfiltered, Real-World Event Streams
- Includes all auction transitions, halts, short sale restrictions, and trading status changes.
- No filtered or missed data, so your strategy is tested against true market conditions.
- Prevents curve-fitting based on unrealistic data assumptions.
Recreate Full Order Book Behavior
- Use Level 2 for aggregated price level simulation.
- Use Level 3 for per-order simulation — add, modify, cancel, execute.
- Supports limit/market order behavior, priority modeling, and realistic fill mechanics.
Include Market Interruptions and Edge Cases
- Account for IPO order acceptance, news halts, and circuit breakers.
- Model what happens when liquidity disappears or market structure shifts.
- Test strategies across calm and stressed market regimes.
Optimize Strategy Logic with Clean, Structured Data
- Use clear field names, schema-based typing, and pre-tagged metadata (e.g., is_trade_through_exempt).
- No decoding, parsing, or reverse-engineering from cryptic formats.
- Fast time-to-value for quant teams and algo developers.