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Options Strategy Backtesting Simulator for Retail
A web-based backtesting platform that lets retail investors simulate options income strategies over 20+ years of historical market data. Users input tickers, strike distances, holding periods, and position sizing to see realistic net CAGR, maximum drawdown, assignment frequency, and comparison to buy-and-hold benchmarks. The tool addresses the critical gap between perceived premium yields (13.2%) and actual returns (5.5%) that no consumer tool currently exposes.
Why this matters
Retail investors selling puts see attractive premium yields but have no accessible way to verify actual historical returns after assignment losses. Research from a major investment bank demonstrated that put-selling at 10% OTM collected about 13.2% annually in premiums but delivered only 5.5% CAGR over 27 years — dramatically lower than the 9.2% buy-and-hold benchmark. Newcomers lack tools to input their specific strike, ticker, and holding period and see realistic expected returns. They turn to generic AI chatbots and forum advice instead, receiving inconsistent and sometimes dangerous guidance. The core failure is that headline premium numbers look like free money, but the actual experience includes assignment events, drawdowns, and opportunity costs that no consumer tool makes visible before capital is committed.
- · Built for Retail investors with portfolios of $50K-$2M who are considering options income strategies, particularly those approaching or in early retirement seeking yield, and windfall recipients exploring put-selling as a capital deployment strategy.
- · Most likely monetization: Freemium SaaS subscription with free tier for basic index backtesting and premium tier ($29-49/month) for custom tickers, multi-leg strategies, and portfolio-level simulation.
The Pain · Narrative
Retail investors selling puts see attractive premium yields but have no accessible way to verify actual historical returns after assignment losses. Research from a major investment bank demonstrated that put-selling at 10% OTM collected about 13.2% annually in premiums but delivered only 5.5% CAGR over 27 years — dramatically lower than the 9.2% buy-and-hold benchmark. Newcomers lack tools to input their specific strike, ticker, and holding period and see realistic expected returns. They turn to generic AI chatbots and forum advice instead, receiving inconsistent and sometimes dangerous guidance. The core failure is that headline premium numbers look like free money, but the actual experience includes assignment events, drawdowns, and opportunity costs that no consumer tool makes visible before capital is committed.
Score Breakdown
Market Signal
Go-to-Market
Retail investors aged 35-60 with $100K-$2M portfolios who are actively researching put-selling strategies on investing communities and YouTube
500K-1M users in the target segment globally
Investing YouTube creators and finance communities — partner with content creators who can demonstrate the backtesting gap visually
$29/month for premium tier
500 registered users within 30 days of launch with at least 20% running backtests on custom parameters, indicating genuine engagement beyond curiosity
MVP Scope · 1–2 weeks
- Build core backtesting engine for single-leg put selling on SPY with 20-year historical options data
- Display net CAGR, max drawdown, assignment rate, and side-by-side comparison with buy-and-hold in a clean results dashboard
- Deploy as a simple web app with one strategy input form (ticker, strike distance, DTE, date range)
- Add plain-language annotations explaining each metric and why headline premiums differ from actual returns
- Set up basic user authentication and save/retrieve backtest configurations
- Add QQQ and VOO support with pre-configured strike distance presets (5%, 10%, 15%, 20% OTM)
- Add multiple holding period options (weekly, monthly, quarterly) with comparison table showing how results change across parameters
- Implement covered call backtesting at identical strikes for direct CSP-vs-covered-call comparison
- Add dividend and interest-on-cash integration into net return calculations
- Create shareable backtest result pages for organic distribution through investing communities
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Historical options data licensing costs may be prohibitive at early stage, making the free tier unsustainable before reaching subscriber volume (strongest risk)
- 2Users may expect brokerage integration and automated order execution, creating feature creep that distracts from the core backtesting value proposition
- 3Free alternatives like spreadsheets, broker-provided tools, or YouTube education may suffice for the majority of users, limiting conversion to paid tiers
Evidence Summary
How AI synthesized this insight — no verbatim quotes
A commenter cited 27 years of research from a major investment bank showing the dramatic gap between 13.2% annual premium collection and 5.5% actual CAGR for put-selling strategies. Another user manually compiled backtest statistics across different deltas and expiration windows to prove a point — exactly the kind of analysis a tool should automate. Multiple commenters discussed comparing cash-secured put returns against covered calls at identical strikes while factoring in dividends and interest, a multi-variable analysis no consumer tool currently handles. The original poster continued refining their put-selling approach despite warnings, demonstrating persistent demand for data-driven validation.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Validate
Promising signals, but needs confirmation. Create a landing page, collect email sign-ups, then decide.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Options Strategy Backtesting Simulator for Retail
Sub-headline
A web-based backtesting platform that lets retail investors simulate options income strategies over 20+ years of historical market data. Users input tickers, strike distances, holding periods, and position sizing to see realistic net CAGR, maximum drawdown, assignment frequency, and comparison to buy-and-hold benchmarks. The tool addresses the critical gap between perceived premium yields (13.2%) and actual returns (5.5%) that no consumer tool currently exposes.
Who It's For
For Retail investors with portfolios of $50K-$2M who are considering options income strategies, particularly those approaching or in early retirement seeking yield, and windfall recipients exploring put-selling as a capital deployment strategy
Feature List
✓ Historical backtesting engine for put selling, covered calls, and spreads on major indices and ETFs with 20+ year data ✓ Net CAGR, max drawdown, assignment frequency, and side-by-side buy-and-hold comparison ✓ Multiple strike distance presets (5%, 10%, 15%, 20% OTM) and holding period options (weekly, monthly, quarterly) ✓ Tax drag, dividend, and interest-on-cash integration into net return calculations ✓ Plain-language annotations explaining the gap between headline premiums and actual returns
Where to Validate
Share your landing page in r/r/options — that's exactly where these pain points were discovered.
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