How to Find High Probability Trades (Step-by-Step Framework)
Written by
A Sign Of Time
Head of Education & Toodegrees Analyst
Key Summary
- High probability trades come from alignment across structure, liquidity, and timing.
- Most traders fail by focusing on entries instead of context.
- A repeatable framework removes subjectivity and improves consistency.
- Using structured tools creates a process-driven approach to trade selection.
What Makes a Trade High Probability?
Finding high probability trades is not about identifying a single perfect setup. It is about building a process that filters noise and focuses on alignment.
Most traders focus on entries. But entries without context are random. The real question is not where to enter — but whether the environment supports a high-probability outcome.
Step 1: Define Direction
High probability trades start with a clear directional bias. The HTF Power Of Three° maps accumulation, manipulation, and expansion phases. This defines whether the current environment supports long or short trades.
Step 2: Identify the Target
Every trade needs an objective. The Liquidity Depth° maps buy-side and sell-side liquidity. This defines where price is likely to go and provides a clear target for the trade.
Step 3: Align with Timing
Most traders ignore timing. The Session Statistical Mapping° defines session-based behavior, manipulation phases, and expansion windows. This ensures trades are taken during high-probability time periods.
Step 4: Confirm with Context
Context adds confidence. The Fractal Consolidations° identifies accumulation zones and compression phases. These provide structural context that supports the trade thesis.
Step 5: Execute with Precision
Entry should be the last step, not the first. The Inversion FVG° refines entries by mapping imbalance and inversion zones. This allows for precise risk definition and better positioning.
Step 6: Filter for Volatility
Many losses occur in low-volatility conditions, not bad direction. The Statistical Volatility° identifies expansion conditions, volatility spikes, and displacement, so low-probability environments get filtered out before entry rather than after.
Step 7: Manage with Data
Risk management should be data-driven. The Average Range Levels° quantifies expected price movement. This ensures targets are realistic and stops are appropriately placed.
Next Steps
→ Stop focusing on entries first
→ Build a structured process from direction to execution
→ Only trade when all steps align
→ Focus on process over outcome
Key Questions
Alignment across direction, liquidity, timing, context, execution, and volatility conditions. No single factor creates high probability — it comes from confluence.
Because they focus on finding entries instead of building a process that evaluates the entire trading environment.
By following a structured framework that defines direction, target, timing, context, entry, volatility conditions, and risk management.
High Probability Trade Framework
| Step | Component | Tool | Purpose | Output |
|---|---|---|---|---|
| 1 | Direction | HTF Power Of Three° | Define bias | Narrative |
| 2 | Target | Liquidity Depth° | Identify objective | Draw on liquidity |
| 3 | Timing | Session Statistical Mapping° | Align with session | Execution window |
| 4 | Context | Fractal Consolidations° | Confirm structure | Setup zone |
| 5 | Entry | Inversion FVG° | Refine execution | Entry level |
| 6 | Conditions | Statistical Volatility° | Filter environment | Valid setup |
| 7 | Risk | Average Range Levels° | Manage expectations | SL / TP |
Professional trading increasingly emphasizes process-driven approaches where multiple independent variables must align before execution. This probabilistic framework mirrors institutional decision-making methods.
Frequently Asked Questions
Yes, all Toodegrees indicators are built exclusively for TradingView. They work on all TradingView plans including the free tier.
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