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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.
이것이 중요한 이유
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 reports을(를) 위해 제작되었습니다.
- · 가장 유력한 수익화 모델: SaaS subscription with tiered pricing based on alert volume and number of strategies backtested.
고충 · 내러티브
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.
점수 세부
시장 신호
시장 진출 전략
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 범위 · 1~2주
- 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
차별화
실패 가능 요인
자가 반박 — 가장 중요한 신뢰 신호
- 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
근거 요약
AI가 이 인사이트를 합성한 방법 — 직접 인용 없음
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.
액션 플랜
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권장 다음 단계
개발 시작
강한 수요 신호 감지. 실제 고통과 지불 의지 확인 — MVP 개발을 시작하세요.
랜딩 페이지 카피 키트
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헤드라인
Realistic Fill Backtesting Engine for Options
서브 헤드라인
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.
대상 사용자
대상: Semi-professional options traders and options alert service operators who need credible, fill-realistic performance metrics for their strategies and subscriber-facing reports
기능 목록
✓ 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
어디서 검증할까요
r/r/options에 랜딩 페이지 링크를 공유하세요 — 바로 이 고통이 발견된 곳입니다.
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