R
Range Mapping
- Define high/low boundaries before you risk capital.
- Avoid center-range entries with weak reward-to-risk.
Range Dominator
Master your range. Dominate your risk.
Trading plan first. Execution second.
Build a plan that survives the rules.
Range Dominator turns Monte Carlo simulation into practical, rule-based decisions so you can execute with discipline and avoid gambling behavior.
- Conservative by design: risk capped at 1.00%
- Quick Risk auto-load for instant onboarding
- Visual pass/fail probability outputs
- Action checklists and learning hub content
Core Capabilities
G
Guardrails
- Respect daily, overall, and trailing loss constraints.
- Keep recommendations capped at 1.00% risk/trade.
M
Monte Carlo Clarity
- See pass/fail pressure before live execution.
- Use percentile paths instead of single-point predictions.
Guided Workflow
Run all 4 steps nowStep 1
Define edge
Set win rate, average win/loss in R, and risk/trade assumptions.
Step 2
Apply rules
Load prop-firm constraints and enforce non-negotiable limits.
Step 3
Run simulations
Generate many paths to estimate breach and pass probabilities.
Step 4
Improve plan
Tune risk size and checklist behavior from output feedback.
Learning Hub
Tool and education in one loop
Micro-course • Beginner • 45-60 min
Micro-Course: Range-Bound Trading Foundation
Build a repeatable process for identifying and trading within structured market ranges.
Track lessonsMicro-course • Intermediate • 60-75 min
Micro-Course: Rule-Based Risk Management System
Engineer a non-negotiable risk process that respects prop-firm limits and your own psychological bandwidth.
Track lessonsArticle • 7 min
How To Define A Tradeable Range Before You Risk Capital
Open articleArticle • 8 min
Rule-Based Risk Management For Prop-Firm Constraints
Open articleArticle • 6 min
Expectancy vs Win Rate: What Actually Keeps You In The Game
Open articleFAQ
Can beginners use this?
Yes. Start with Quick Risk and follow the 4-step guided flow in the calculator.
Why keep risk at or below 1%?
Higher sizing can quickly increase breach probability and resembles gambling behavior under prop-firm rules.
Do I need quant skills for Monte Carlo?
No. Range Dominator translates probability outputs into direct execution guidance.
Ready to execute with discipline?
Load the starter profile and run your first Monte Carlo simulation in under a minute.