Phase 1 is where this either becomes a real system or stays an idea. We’re going to keep it simple, structured, and irreversible (in a good way).
You are NOT installing AI yet. You are building the data spine everything else depends on.
🎯 Goal of Phase 1
By the end of this phase you will have:
- a clean external or internal folder system
- standardized strategy format
- structured backtest + trade data organization
- defined “market regimes”
- a system that is ready for AI (but not using AI yet)
Think of this as building the training brain’s skeleton
📁 STEP 1 — CREATE ROOT DIRECTORY
On your MacBook Pro (preferably external SSD):
AI_TRADING_SYSTEM/
Inside it, create this exact structure:
AI_TRADING_SYSTEM/
│
├── 00_INBOX/
├── 01_STRATEGIES/
├── 02_BACKTESTS/
├── 03_TRADES/
├── 04_REGIMES/
├── 05_MARKET_DATA/
└── 99_ARCHIVE/
🧠 STEP 2 — DEFINE YOUR STANDARD STRATEGY TEMPLATE
Inside:
01_STRATEGIES/
Create a file:
📄 strategy_template.md
Use this format:
# Strategy Name
## Core Idea
What is the market hypothesis?
## Entry Rules
- Condition 1
- Condition 2
## Exit Rules
- Condition 1
- Condition 2
## Timeframe
- (e.g., 1h, daily)
## Market Type
- Trend / Mean Reversion / Volatility / Options / Hybrid
## Assumptions
- Works when...
- Fails when...
## Risk Logic
- Stop loss method
- Position sizing logic
## Notes
- Observations
👉 This becomes your “AI-readable language”
📊 STEP 3 — DEFINE BACKTEST FORMAT (VERY IMPORTANT)
Inside:
02_BACKTESTS/
Every strategy must eventually have:
📄 standardized CSV format:
date, strategy, symbol, entry_price, exit_price, pnl, return_pct, drawdown, regime
📄 AND a summary file:
summary_metrics.json
Example:
{
"strategy": "momentum_breakout_v1",
"sharpe_ratio": 1.2,
"max_drawdown": -15.3,
"win_rate": 0.54,
"avg_trade": 0.8,
"best_regime": "high_volatility"
}
📈 STEP 4 — DEFINE MARKET REGIMES
Inside:
04_REGIMES/
Create these baseline categories:
bull_market/
bear_market/
sideways_low_vol/
high_volatility/
crisis_event/
Each regime folder contains:
regime_definition.md
# High Volatility Regime
## Definition
- VIX above X (you define later)
- Large daily swings
## Characteristics
- frequent breakouts
- higher false signals
## Strategy Behavior
- momentum tends to outperform
- mean reversion degrades
👉 You are teaching the AI how to THINK about markets
📂 STEP 5 — CREATE TRADES FORMAT
Inside:
03_TRADES/
Standardize your raw trade logs:
date, symbol, strategy, direction, entry, exit, pnl, notes, regime
👉 This is your raw truth layer
📊 STEP 6 — MARKET DATA PLACEHOLDER
Inside:
05_MARKET_DATA/
Start simple:
SPY.csv
QQQ.csv
VIX.csv
macro_notes.md
You don’t need anything advanced yet.
📥 STEP 7 — INBOX RULE (VERY IMPORTANT)
Everything new goes here first:
00_INBOX/
Rules:
- never analyze files directly from inbox
- always move them into proper folders first
- clean → structure → then analyze
🧠 STEP 8 — ARCHIVE RULE
99_ARCHIVE/
Move:
- old strategies
- failed experiments
- deprecated backtests
👉 This prevents system clutter
⚙️ PHASE 1 SUCCESS CRITERIA
You are done when:
✔ You can drop any new strategy into a structured folder
✔ You have consistent CSV format for trades
✔ You have defined regimes (even if simple)
✔ You can explain any strategy in the template format
✔ You can separate raw vs structured data
🚫 WHAT YOU DO NOT DO YET
Do NOT:
- install LLMs yet
- build dashboard
- build RAG system
- optimize anything
- overthink models (7B/14B/20B)
👉 That comes AFTER structure exists
🧠 WHY PHASE 1 MATTERS (MOST IMPORTANT INSIGHT)
Without this phase:
AI = random guessing over messy files
With this phase:
AI = structured trading analyst grounded in consistent data
🏁 FINAL SUMMARY
Phase 1 is about building a clean, structured trading data foundation that AI can reliably reason over later
💡 One-line takeaway
If your data is structured, your AI becomes useful. If it isn’t, no model will save it.