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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.
これが重要な理由
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.
- · Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports向けに構築。
- · 最も可能性の高い収益化モデル: SaaS subscription with tiered pricing based on alert volume and number of strategies backtested。
痛み · ナラティブ
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.
スコア内訳
市場シグナル
市場投入
Independent options alert service operators with 50-500 paying subscribers who need credible fill-realistic performance to retain and grow their subscriber base
Several thousand alert service operators and tens of thousands of serious retail options backtesters globally
Organic presence in options trading communities and targeted outreach to alert service operators
$49/month for individual backtesters, $149/month for alert service operators with public grading
15 paying users within 30 days of launch, with at least 3 alert service operators using the public grading badge
MVPの範囲 · 1～2週間
- 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
- 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
差別化
失敗する可能性がある理由
自己反論 — 最も重要な信頼のシグナル
- 1Premium options data feed costs ($500-2000/month) may make pricing prohibitive for individual traders, squeezing margins before reaching scale
- 2Established backtesting platforms like Thinkorswim, TradeStation, or OptionAlpha could add realistic-fill features relatively quickly, neutralizing the differentiation
- 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
エビデンスの概要
AIがこのインサイトをどのように統合したか — 逐語的な引用はありません
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.
アクションプラン
コードを書く前に、この機会を検証しましょう
推奨する次のステップ
開発する
強い需要シグナルを検出。本物の課題と支払い意欲を確認 — MVPの開発を始めましょう。
ランディングページ文案キット
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見出し
Realistic Fill Backtesting Engine for Options
サブ見出し
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.
ターゲットユーザー
対象：Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports
機能リスト
✓ 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
どこで検証するか
r/r/options にランディングページのリンクを投稿しましょう — そこがこの課題が発見された場所です。
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