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Active traders repeatedly experience getting stopped out by routine volatility and liquidity sweeps, then watching price continue in their original direction. This creates measurable performance drag (many small losses, missed winners) and a confidence spiral, because traders can’t tell whether the issue is stop placement, entry timing, or market microstructure.
Stop-Loss Forensics Studio
A trading post-mortem and journaling web app that automatically classifies stop-outs (noise vs. structure break vs. sweep) and quantifies how alternative stop placements would have changed outcomes. Users connect their broker/export trades, and the app reconstructs the stop-out context with volatility bands, nearby liquidity levels, and time-of-day patterns to produce actionable rules like "minimum stop distance = X ATR in first 30 minutes".
Active retail day traders and small prop-style traders (manual execution) who trade equities/options intraday and suffer frequent stop-outs and inconsistent results.
The post shows a recurring, emotionally and financially costly issue: stops get hit repeatedly, then trades work without them. The product addresses this by turning each stop-out into structured evidence: quantify whether stops are systematically too tight, placed at obvious levels, or entered too early, then recommend concrete, testable stop/entry rules tailored to the user’s instrument and timeframe.
Free stop-out audit: upload 20 trades and get a PDF showing top 3 stop-out patterns and one rule to test
$19 one-time "30-day Stop-Out Report" with deeper segmentation by ticker/session/setup tag
$49-$99/month subscription for continuous journaling, counterfactual testing, and rule tracking by setup
Add-on $29/month for advanced exports, weekly digest, and multi-account tracking
$1,500-$5,000/year team license for small trading groups with shared templates, anonymized benchmarking, and admin controls
MVP is feasible with a small team: broker CSV imports (IBKR/Tradovate/Thinkorswim exports), price/volatility data from a market data vendor, and rule-based analytics (no dependency on generative AI). Key risks: data quality across brokers and avoiding any language that constitutes personalized investment advice—position as analytics/journaling with user-controlled rules.
TAM: ~1.5M-3M active retail day traders globally; SAM (English-speaking, pays for tools): ~150k-400k. At $60/month ARPU, a 5k-customer niche yields ~$3.6M ARR.
Strong journaling but limited microstructure-oriented diagnosis; insights are generic and require manual interpretation
No stop-out sweep detection, limited counterfactual stop placement simulation
Intraday equity/options traders who need stop placement rules by session and volatility regime
Feature-rich but complex; users still must manually infer why stop-outs happen
Lacks opinionated stop-loss forensics workflows and automated pattern-to-rule recommendations
Traders who want prescriptive, testable stop/entry rule outputs rather than dashboards
Desktop-heavy workflow and manual data entry for many users; less integrated with modern broker exports
No automated volatility/structure labeling around stop-outs; weak counterfactual tooling
Newer active traders who will pay for automation and broker-connected analysis
Narrow wedge: become the best-in-class tool specifically for stop-loss placement and stop-out root-cause analysis (not a generic journal). Win by producing clear, testable rules from the user’s own history (counterfactual P&L/expectancy), with minimal setup and strong broker import support.
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