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78score
r/options
SaaS subscription with tiered pricing based on alert volume and number of strategies backtested
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Realistic Fill Backtesting Engine for Options

A SaaS backtesting and alert validation platform that defaults to realistic bid/ask fill assumptions instead of mid-price, allowing options traders and alert service operators to measure true strategy performance. Includes historical spread analysis by strike and moneyness, real-time spread monitoring, and auto-filtering of untradeable setups.

En hausse +105%4 canauxTendance des mentions sur 30 jours: latest 23, peak 33, 30-day series
Voir sur Reddit
Découvert 9 oct. 2026

Pourquoi c'est important

You run an options alert service or actively backtest strategies, and your numbers look fantastic on paper — 90% win rates, +20% average returns. But when you actually trade your own signals, buying at the ask and selling at the bid, the spread devours your edge and you are left at breakeven. The far-OTM plays that looked brilliant in backtesting are the worst culprits: market makers widen those spreads to absurd levels during moves, making them untradeable despite correct directional calls. You have started manually logging spreads and filtering to near-the-money strikes, but you have no automated way to validate whether your alerts are actually tradeable at realistic fills before publishing them to subscribers.

  • · Conçu pour Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports.
  • · Monétisation la plus probable : SaaS subscription with tiered pricing based on alert volume and number of strategies backtested.

La douleur · Récit

You run an options alert service or actively backtest strategies, and your numbers look fantastic on paper — 90% win rates, +20% average returns. But when you actually trade your own signals, buying at the ask and selling at the bid, the spread devours your edge and you are left at breakeven. The far-OTM plays that looked brilliant in backtesting are the worst culprits: market makers widen those spreads to absurd levels during moves, making them untradeable despite correct directional calls. You have started manually logging spreads and filtering to near-the-money strikes, but you have no automated way to validate whether your alerts are actually tradeable at realistic fills before publishing them to subscribers.

Détail du score

Intensité du problème9/10
Volonté de payer7/10
Facilité de réalisation5/10
Durabilité7/10

Signal du marché

Tendance des mentions sur 30 joursPic : 33
Sparkline: latest 23, peak 33, 30-day series
Canaux couverts
optionsDaytradingalgotradingValueInvesting

Mise sur le marché

Utilisateur cible exact

Independent options alert service operators with 50-500 paying subscribers who need credible fill-realistic performance to retain and grow their subscriber base

Nombre d'utilisateurs estimé

Several thousand alert service operators and tens of thousands of serious retail options backtesters globally

Canal d'acquisition principal

Organic presence in options trading communities and targeted outreach to alert service operators

Ancre de prix

$49/month for individual backtesters, $149/month for alert service operators with public grading

Premier jalon

15 paying users within 30 days of launch, with at least 3 alert service operators using the public grading badge

Périmètre MVP · 1–2 semaines

Semaine 1
  • Set up Polygon.io or ORATS options data integration for historical bid/ask quotes
  • Build core backtesting engine that evaluates strategies at buy-at-ask/sell-at-bid instead of mid-price
  • Create spread analysis module that calculates spread-to-edge ratio for each historical trade
  • Design simple web dashboard showing mid-price vs. realistic-fill performance comparison
  • Build API endpoint to ingest strategy parameters and return fill-realistic backtest results
Semaine 2
  • Add historical spread database with filtering by underlying, strike, DTE, and moneyness
  • Implement auto-filtering that flags and removes untradeable far-OTM setups from backtest results
  • Create alert grading report that operators can share with subscribers showing realistic fill metrics
  • Build comparison view showing strategy performance across strike zones (far-OTM vs. near-ATM vs. ITM)
  • Add real-time spread monitor that checks current spread conditions before a signal is published
Fonctions MVP: Backtesting engine using buy-at-ask/sell-at-bid fill assumptions by default · Historical spread database searchable by underlying, strike, DTE, and market condition · Spread-to-edge ratio scoring that flags strategies as tradeable or untradeable · Alert grading dashboard that publishes realistic fill performance alongside mid-price metrics · Real-time spread monitor that warns when current spreads make a signal untradeable

Différenciation

Solutions existantes
Thinkorswim (Schwab)FidelityTraditional backtesting platforms (unspecified)
Notre angle
No brokerage-agnostic tool exists that combines realistic bid/ask fill backtesting, real-time spread monitoring, and cross-platform walk-limit order automation for options traders

Pourquoi cela pourrait échouer

Auto-contre-argument — le signal de confiance le plus important

  1. 1Premium options data feed costs ($500-2000/month) may make pricing prohibitive for individual traders, squeezing margins before reaching scale
  2. 2Established backtesting platforms like Thinkorswim, TradeStation, or OptionAlpha could add realistic-fill features relatively quickly, neutralizing the differentiation
  3. 3Options data licensing restrictions may prevent redistributing spread analytics to subscribers, limiting the alert-service-operator use case that has the highest willingness to pay

Résumé des preuves

Comment l'IA a synthétisé cet aperçu — pas de citations textuelles

Approximately 8 commenters described the core problem: strategies and alerts that look excellent at mid-price become breakeven or negative at realistic bid/ask fills. Multiple users confirmed they manually track spreads alongside signals and filter to near-the-money strikes to preserve tradeable win rates. Several noted that far-OTM contracts are the worst offenders, with market makers widening spreads dramatically during moves. The discussion revealed that no automated solution exists for validating alerts at realistic fills — users are doing this manually with spreadsheets and ad-hoc logging.

1 1 publication analysée4 4 canauxAI · Synthétisé par IA · pas de citations

Plan d'Action

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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 Fill Backtesting Engine for Options

Sous-titre

A SaaS backtesting and alert validation platform that defaults to realistic bid/ask fill assumptions instead of mid-price, allowing options traders and alert service operators to measure true strategy performance. Includes historical spread analysis by strike and moneyness, real-time spread monitoring, and auto-filtering of untradeable setups.

Pour Qui

Pour Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports

Liste des Fonctionnalités

✓ Backtesting engine using buy-at-ask/sell-at-bid fill assumptions by default ✓ Historical spread database searchable by underlying, strike, DTE, and market condition ✓ Spread-to-edge ratio scoring that flags strategies as tradeable or untradeable ✓ Alert grading dashboard that publishes realistic fill performance alongside mid-price metrics ✓ Real-time spread monitor that warns when current spreads make a signal untradeable

Où Valider

Partagez votre landing page sur r/r/options — c'est exactement là que ces points de douleur ont été découverts.

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Questions fréquentes

Qui rencontre ce problème ?
Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports
Est-ce une réelle opportunité ?
Cette opportunité obtient un score de 78/100 selon la métrique composite de Pain Spotter (intensité du problème, propension à payer, faisabilité technique et viabilité). Validez-la davantage avant d'y consacrer du temps de développement.
Comment dois-je la valider ?
Menez 5 entretiens de découverte client avec le public cible, publiez une landing page avec une liste d'attente, et vérifiez l'activité récente sur le post source lié avant de commencer le développement.