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Realistic Execution Simulator API
Create a simulation layer that adds configurable slippage, spread, liquidity, financing, and fill assumptions to paper trading and backtests. This solves the core trust problem: traders want to know whether apparent edge survives under more realistic execution conditions.
Pourquoi c'est important
If your strategy looks great in a simulated account, you still do not know whether it survives contact with the market. You worry that favorable fills, ignored spreads, missing interest costs, and unrealistic liquidity assumptions are making a weak system look strong. The more frequently you trade, the more dangerous this gap becomes. Without a credible way to model execution friction, you are left guessing whether the paper gains are real or just artifacts of the simulator. That uncertainty blocks live deployment and creates endless debates about whether performance came from edge or from a forgiving environment.
- · Conçu pour Retail quants, options traders, and small automated trading teams who already run paper strategies and need more credible performance validation before going live..
- · Monétisation la plus probable : API subscription.
La douleur · Récit
If your strategy looks great in a simulated account, you still do not know whether it survives contact with the market. You worry that favorable fills, ignored spreads, missing interest costs, and unrealistic liquidity assumptions are making a weak system look strong. The more frequently you trade, the more dangerous this gap becomes. Without a credible way to model execution friction, you are left guessing whether the paper gains are real or just artifacts of the simulator. That uncertainty blocks live deployment and creates endless debates about whether performance came from edge or from a forgiving environment.
Détail du score
Signal du marché
Mise sur le marché
First buyers are technically fluent traders already using broker APIs and backtesting tools but unhappy with simplistic fill assumptions.
10,000-25,000 highly relevant early users willing to test an execution realism layer
Python package plus technical blog posts comparing naive and realistic paper results
$79/month
Get 10 paying users to run at least three strategies through the simulator and report changed go-live decisions
Périmètre MVP · 1–2 semaines
- Define execution model inputs for spread, slippage, fees, and financing
- Build REST API and Python SDK for simulation jobs
- Implement equity and option trade-cost modules
- Add configurable presets for common strategy styles
- Create comparison output between naive and realistic results
- Integrate historical quote data for spread-aware fills
- Add liquidity caps and partial-fill logic
- Build browser dashboard for uploading strategy trades
- Publish documentation with validation examples
- Run pilot tests with a small set of active traders
Différenciation
Pourquoi cela pourrait échouer
Auto-contre-argument — le signal de confiance le plus important
- 1Users may expect institution-grade modeling that is expensive to deliver at startup scale.
- 2Without trusted benchmark data, simulation outputs may be challenged as arbitrary.
- 3Some users may prefer established backtest stacks instead of adding another layer.
Résumé des preuves
Comment l'IA a synthétisé cet aperçu — pas de citations textuelles
Execution realism was the most frequently reinforced theme across the discussion, with repeated concerns about slippage, favorable fills, financing costs, and the general unreliability of paper results. The combination of high pain intensity, broad mention frequency, and skepticism toward headline performance suggests a strong market need for a realism-focused validation layer.
Plan d'Action
Validez cette opportunité avant d'écrire du code
Prochaine Étape Recommandée
Construire
Signaux de demande forts. Vraie douleur et volonté de payer détectées — commencez à construire un MVP.
Kit de Textes pour Landing Page
Textes prêts à coller, basés sur le langage réel de la communauté Reddit
Titre Principal
Realistic Execution Simulator API
Sous-titre
Create a simulation layer that adds configurable slippage, spread, liquidity, financing, and fill assumptions to paper trading and backtests. This solves the core trust problem: traders want to know whether apparent edge survives under more realistic execution conditions.
Pour Qui
Pour Retail quants, options traders, and small automated trading teams who already run paper strategies and need more credible performance validation before going live.
Liste des Fonctionnalités
✓ Slippage and spread models by asset and strategy type ✓ Commission and overnight financing assumptions ✓ Liquidity and order-size impact controls ✓ Scenario templates for conservative, baseline, and optimistic fills ✓ Backtest and paper-trade result comparison reports
Où Valider
Partagez votre landing page sur r/r/algotrading — c'est exactement là que ces points de douleur ont été découverts.
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