Last Updated: July 12, 2025
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Overview
This module delivers risk-aware identification of recurring market reaction patterns following similar historical events. It helps anticipate potential price movements and volatility shifts based on past event precedents.
The RISI Framework Breakdown for Historical Event Pattern Recognition
| Step | Name | Purpose |
|---|---|---|
| R | Role | Sets the AI’s posture and persona as an institutional historical event analyst. |
| I | Insight | Analyzes past market reactions and volatility patterns following comparable events. |
| S | Strategy | Simulates probable market moves and trade setups based on historical event patterns. |
| I | Impact | Provides actionable guidance on trade planning and risk management using historical insights. |
How to Use the Historical Event Pattern Recognition Module
Copy and paste these prompts into ChatGPT sequentially, replacing [TARGET] with your target event:
What to enter for [TARGET]:
State your target event, e.g.:
- “Earnings Releases,”
- “Product Launches,”
- “Regulatory Announcements,”
- Or, “Economic Reports.”
- Role Prompt:
Activate ProEventTrade Mode for Institutional Historical Event Analysis - Pattern Analysis Prompt:
Summarize typical market reaction patterns following events similar to [TARGET]. Limit output to one paragraph. - Volatility Pattern Prompt:
Analyze volatility and price behavior after comparable past events. Limit output to one paragraph. - Strategy (Simulation) Prompt:
Simulate trade setups and risk scenarios based on historical event patterns. Limit output to one paragraph. - Impact (Implications) Prompt:
Summarize actionable recommendations for trade planning based on historical event analysis. Provide one clear, actionable paragraph grounded in institutional behavior.
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