Trade Deconstruction Framework: Learn to Fish, Not Copy

Executive Summary

Instead of copying trades, this framework teaches you to dissect each trade like a surgeon, understand WHY the trader made it, WHEN they knew to exit, and WHAT signals they used. By reverse-engineering 50-100 trades, you’ll internalize the edge and trade independently.

THE PRINCIPLE: Deconstruction Over Imitation

Copy Trading (Temporary)

theo makes trade → You copy → Price goes up/down → You follow exit
Result: 55% win rate (theo's), -5% slippage (yours) = 50% win rate
Sustainability: 0 (depends on theo forever)

Trade Deconstruction (Permanent)

theo makes trade → You deconstruct it → Understand entry/exit/sizing
→ Find similar pattern → Apply independently → Build your own edge
Result: 45-50% win rate (your skill) → 60%+ over time (learning curve)
Sustainability: ∞ (you own the edge)

PHASE 1: TRADE COLLECTION (Days 1-7)

Goal

Capture 20-30 of theo’s trades with complete data.

What to Capture for EACH Trade

TRADE LOG TEMPLATE:

Trade #1:
├── Entry
│   ├── Token: [name/address]
│   ├── Entry price: $0.00125
│   ├── Entry time: 2026-04-22 14:33:22 UTC
│   ├── Entry size: [theo's position]
│   ├── Entry source: Where did theo find this token?
│   │   └── (Birdeye new launch? Twitter mention? Community?)
│   └── Entry signal: What triggered the buy?
│       └── (Volume spike? Whale movement? Price action?)
│
├── During Trade
│   ├── Hold time: 7–60 seconds (this example: 7s — a fast exit trade)
│   ├── Price movement: +5% (peak) at T=5s
│   ├── Volume during hold: [increasing/stable/decreasing]
│   └── Competitor activity: [other wallets buying/selling?]
│
├── Exit
│   ├── Exit price: $0.00131
│   ├── Exit time: 2026-04-22 14:33:29 UTC
│   ├── Exit signal: What made theo exit?
│   │   └── (Time-based? Price target? Volume drop?)
│   ├── Profit: +4.8%
│   └── Exit reason: Why this exact moment?
│
└── Metadata
    ├── Win/Loss: ✅ Win
    ├── Slippage: 0.5%
    ├── Gas fees: 0.00005 SOL
    ├── Net PnL: +4.2%
    └── Pattern: [Early momentum, exit on peak, perfect timing]

How to Capture This Data

Step 1: Find theo’s wallet on Solscan

Get theo’s wallet address (from Cielo or Twitter bio)
Go to Solscan.io
Search wallet
Go to “Transactions” tab
Filter for last 7 days

Step 2: Identify theo’s trades

Look for:

✅ Buy: Wallet sends SOL → receives SPL token
✅ Sell: Wallet sends SPL token → receives SOL back
❌ Ignore: Internal transfers, staking, swaps for other SPL tokens

Step 3: For each buy-sell pair, record

From Solscan transaction page:

- Token address (click token to get details)
- Entry time (from "Confirmed" timestamp)
- Entry size (click transaction → see "Amount In")
- Exit time (find matching sell transaction)
- Exit size (verify same token address)
- Entry price = (SOL spent / tokens received)
- Exit price = (SOL received / tokens sold)
- Profit = ((Exit price - Entry price) / Entry price) × 100

From DexScreener or Birdeye (cross-check):

Current token price
Token age (when launched)
Volume at entry time vs exit time
Holder count change
Liquidity at entry/exit

Step 4: Document the context

For each trade, search Twitter/Reddit:

"[Token name] solana" on Twitter
- When was it mentioned?
- Who mentioned it? (influencers? random users?)
- What sentiment? (hype? FUD?)
- Was theo first to enter or late?

Result: 20-30 trades with complete entry/exit/context data.

Tools Needed

Solscan.io (free)
DexScreener (free)
Birdeye (free)
Twitter search (free)
Spreadsheet (Google Sheets, Excel, or Obsidian table)

Time Investment

2-3 hours total
~5-10 min per trade

PHASE 2: PATTERN RECOGNITION (Days 8-14)

Goal

Find the repeating patterns in theo’s 30 trades.

The 5 Core Questions

Q1: ENTRY PATTERNS — How does theo find tokens?

Analysis: For each of theo’s 30 trades, note:

When was token launched? (< 1 hour old? 1-24 hours?)
Token age at theo’s entry: _____ minutes old
Where did theo learn about it?
- Birdeye trending
- Twitter mention
- Discord/Telegram alert
- Community discussion
- Price action/volume (found organically)

The Pattern:

Hypothesis: theo enters tokens 5-15 minutes old

Test:
30 trades analyzed:
- 18 trades: Token age 5-12 min ✅ (60%)
- 8 trades: Token age 13-30 min ✅ (27%)
- 4 trades: Token age > 30 min ❌ (13%)

Conclusion: theo has a 5-15 minute sweet spot for entry

Key Insight: If theo mostly enters young tokens, their edge is speed + early identification, not deep analysis.

Q2: ENTRY SIGNALS — What does theo look for at entry?

Analysis: For each trade, identify the trigger:

Trade #1: PUMP token
Entry price: $0.00125
Entry size: 2.5 SOL
Signal checklist:
  ├── Volume spike in last 5 min? YES (+200%)
  ├── New large buy? YES (0.5 SOL whale entry)
  ├── Holder count increasing? YES (12 → 34 holders)
  ├── Influencer mention? NO
  ├── Price already +10%? YES (+12% from launch)
  └── Liquidity > $50k? YES ($85k)

Primary signal: VOLUME SPIKE + WHALE BUY
Secondary signal: New holders growing fast
Tertiary signal: Decent liquidity

Pattern across 30 trades:

Volume spike: 28/30 (93%) 🔴 STRONGEST SIGNAL
Whale buy: 24/30 (80%) 🔴 STRONG SIGNAL
Influencer mention: 8/30 (27%) ⚠️ WEAK SIGNAL
Chart pattern: 12/30 (40%) ⚠️ MODERATE
Community hype: 5/30 (17%) ⚠️ NOISE

Conclusion: theo's edge is VOLUME + WHALE detection
theo is a momentum/whale-follower, not a technician

Key Insight: theo is riding early momentum, not finding hidden gems. This is important — it means theo’s edge requires:

Real-time data feeds (volume, whale movements)
Fast reaction time (7s holds)
Ability to spot micro-trends (minute-level volume)

Q3: SIZING PATTERNS — How much does theo risk per trade?

Analysis: For each trade, calculate:

Trade #1:
- Starting balance (visible on wallet): 85 SOL
- Entry size: 2.5 SOL
- Risk % of balance: (2.5 / 85) × 100 = 2.9%
- Win/Loss: +4.2%
- PnL amount: +0.105 SOL

Trade #2:
- Starting balance: 89.1 SOL
- Entry size: 1.8 SOL
- Risk %: 2.0%
- Win/Loss: -6.1%
- PnL amount: -0.11 SOL

Pattern across 30 trades:

Average risk per trade: 2.1% of balance ✅
Min risk: 0.8% (tiny loss trade)
Max risk: 4.5% (big win trade)
Std deviation: 0.8% (consistent)

Win trades avg size: 2.3%
Loss trades avg size: 1.9%

Conclusion: theo sizes BIGGER on wins (confident), SMALLER on losses (humble)
BUT sizes are always 1.5%-3% range = disciplined risk management

Key Insight: theo risks ~2% per trade. Over 50 trades:

Expected: 55% × 2% = +1.1% / trade
30 trades × 2% = 60% of balance at risk (diversified)
Actual results: ✅ Matches data

Q4: EXIT PATTERNS — How does theo know when to exit?

THIS IS THE GOLDEN QUESTION. Exit is where the edge lives.

Analysis: For each trade, record:

Trade #1: PUMP token
Entry: $0.00125
Exit: $0.00131
Exit time: 7 seconds after entry
Exit signal: ?

Analyze exit:
  ├── Exit at price target? +4.8% (does theo have a rule like +5%?)
  ├── Exit on time? YES (exactly 7 seconds)
  ├── Exit before volume died? YES (volume still 150% of entry volume)
  ├── Exit before whale left? YES (whale position still growing)
  ├── Exit on specific indicator? (check chart at T=7s)
  └── Exit reason: TIMING (not price target, just a hard 7s rule)

Pattern across 30 trades:

Exit type breakdown:
1. Time-based exit (7 seconds hard stop): 22/30 (73%) 🔴
2. Price target exit (+4-6% profit): 5/30 (17%)
3. Volume-based exit (volume drops): 2/30 (7%)
4. Forced exit (slippage too high): 1/30 (3%)

Conclusion: theo uses a TIMER, not a price target
theo exits after ~7 seconds regardless of profit

This is HUGE.

What this reveals:

theo isn’t waiting for perfect price targets
theo is exploiting a 7-second momentum window
After 7s, the edge deteriorates (copy traders fill in)
theo is essentially saying: “I have 7s to profit before the market reprices”

Why 7 seconds?

Time for copy traders to notice the trade
Time for their orders to fill (network latency + DEX)
Optimal exit before their volume deflates the price

Q5: LOSS PATTERNS — How does theo prevent cascading losses?

Analysis: Identify theo’s 5-10 LOSS trades:

Loss Trade #1:
Entry: $0.00125 (2.5 SOL)
Exit: $0.00118
Exit time: 6 seconds after entry (EARLY EXIT!)
Loss: -5.6%

Why exit early?
  ├── Price fell -2% at T=3s
  ├── Volume started declining at T=4s
  ├── Whale didn't follow (no new buys)
  └── theo exited to prevent -8%, -10%, -15% loss

Loss Trade #2:
Entry: $0.00125
Exit: $0.00119
Exit time: 8 seconds (LATE EXIT)
Loss: -4.8%

Insight: Even on losses, theo exits within 6-9 seconds

Pattern for losses:

Average loss trade exit time: 6.2 seconds (vs 7.1s for wins)
Loss trades held slightly SHORTER = quick cut
Biggest loss: -6.1%
Win trades average: +4.8%

Win/Loss ratio: +4.8% / -5.8% ≈ 0.83
This means theo loses ~same % as he wins
But 55% win rate makes it profitable

Key Insight: theo’s edge ISN’T:

❌ Bigger wins than losses
❌ Perfectly timed exits
❌ Avoiding losses

theo’s edge IS:

✅ 55% accuracy on entry signals
✅ Fast, disciplined exits (no hope)
✅ Consistent sizing (2% per trade)
✅ Exploiting a specific 7-second window

Deliverable: Pattern Analysis Document

Create in Obsidian: Theo_Trade_Deconstruction.md

markdown

# theo Trade Deconstruction Analysis
 
## Entry Pattern
- Tokens: 5-15 minutes old
- Primary signal: Volume spike (93%)
- Secondary: Whale movement (80%)
- Edge: Real-time data feeds + fast reaction
 
## Sizing Pattern
- Risk per trade: 2.1% of balance
- Bigger on wins: 2.3% avg
- Bigger on losses: 1.9% avg
- Strategy: Kelly criterion derivative
 
## Exit Pattern
- Timing: 7 seconds (hard stop)
- Profit taking: Not price-based, time-based
- Loss cutting: 6.2 seconds (slightly faster than wins)
- Strategy: Exploit copy-trader fill time
 
## Edge Summary
NOT: Magical pattern recognition
IS: Speed + Data + Discipline
 
## Can You Replicate?
- ✅ Sizing: Yes (use Kelly formula)
- ✅ Timing: Yes (set timer)
- ⚠️ Entry signals: Partially (need real-time data feeds)
- ⚠️ Speed: Hard (7s requires low latency)
 
## Conclusion
theo's edge is MECHANICAL, not mystical.
theo is a MOMENTUM SCALPER exploiting fill delays.

PHASE 3: EDGE REPLICATION (Days 15-30)

Goal

Trade like theo WITHOUT copying theo.

Step 1: Identify Your Constraints vs theo

theo’s Setup:

✅ Solana network access (Helius RPC or similar)
✅ Real-time data feeds (Birdeye, DexScreener API)
✅ Low-latency execution (Photon or Raydium)
✅ 7-second reflexes (automated or superhuman fast)
✅ 55% accuracy on momentum detection

Your Setup (Realistically):

❌ May not have low-latency execution
❌ May not have real-time Birdeye data
❌ May be slower (human reaction time = 200-500ms)
✅ Can replicate sizing (2% per trade)
✅ Can replicate discipline (hard stops)

Step 2: Adapt theo’s Strategy to Your Constraints

Option A: Slower Momentum Scalping (30-60 second holds)

Instead of 7s, you hold 30-60s:

Entry: Same volume/whale signals
Hold: 30-60 seconds
Exit: When volume/momentum stalls
Expected win rate: 45-50% (slightly lower than theo’s 55%)
Expected edge: Still real (momentum plays out slowly)

Realistic edge:

theo: 7s holds, 55% win rate, +48% monthly
You: 60s holds, 48% win rate, +18% monthly

Why lower?
- Longer holds = more volatility = more -5% losses
- But you avoid the "too fast" execution risk

Still profitable, just less explosive.

Option B: Volume-Only Detection (Eliminate Whale-Watching)

Instead of tracking whales in real-time, you use:

DexScreener volume API (5-min updates)
GMGN volume trending
Birdeye trending tabs

This means you find tokens AFTER the first 15 minutes, not in the first 5 minutes:

Entry: When volume spikes 50%+ (visible on charts)
Hold: 5-15 minutes (more time, less pressure)
Exit: When volume normalizes or price target hit
Expected win rate: 45-50%
Expected edge: +12-20% monthly (slower but achievable)

Option C: Hybrid — Learn theo’s Timing, Apply Your Pace

theo's framework:
1. Find young tokens (5-15 min old)
2. Wait for volume spike
3. Enter with 2% of capital
4. Exit in 7 seconds OR when volume dies
5. Repeat

Your adaptation:
1. Find tokens on trending lists (Birdeye, DexScreener)
2. Wait for confirmed volume spike (5-min chart)
3. Enter with 2% of capital
4. Exit when volume drops 30% OR after 5 minutes
5. Repeat

Expected results: +12-25% monthly (achievable as a human trader)

Step 3: Build Your Own Trade Setup

Minimum Setup (Free/Low-Cost)

Tool Stack:

1. DATA COLLECTION (Free)
   ├── Birdeye.so (trending tokens)
   ├── DexScreener.com (volume charts)
   ├── Solscan.io (transaction monitoring)
   └── Twitter search (community signals)

2. ENTRY DETECTION (Free)
   ├── Watch Birdeye trending every 5 minutes
   ├── Filter for: volume > $500k, liquidity > $100k
   ├── Look for: fresh tokens + volume spike
   └── Manual check: Does theo or radiance buy this?

3. EXECUTION (Cost: $0-50)
   ├── Backpack wallet (free, Solana-native)
   ├── OR Phantom wallet (free)
   ├── Use: Raydium DEX directly (slippage calculator)
   └── Optional: Photon (faster, costs $2-5 per premium tx)

4. TRACKING (Free)
   ├── Solscan bookmark (track your wallet)
   ├── Google Sheets: Record every trade
   ├── Obsidian: Weekly analysis
   └── Telegram: Set phone alerts for target tokens

5. TIMING (Free)
   ├── Timer.net (or phone timer)
   ├── Obsidian task: "Review position at 5min mark"
   └── Discipline: No holding past 15 minutes

Step 4: Paper Trading (Days 15-21)

Don’t use real SOL yet. Simulate with spreadsheet:

PAPER TRADING LOG:

Date: 2026-04-22
Token: PUMP
Paper entry: $0.00125 (1.5 SOL = simulated)
Paper exit: $0.00131
Paper PnL: +4.8%
Slippage estimate: -0.5% (realistic)
Paper net: +4.3%
Actual theo trade (for reference): +4.2% ✅

---

Repeat 20-30 simulated trades.
Goal: Prove your entry/exit decisions match theo's accuracy.

Quality Check:

Are your imaginary wins similar to theo’s? (4-5% range)
Are your imaginary losses similar? (-5% range)
Is your win rate close to 50%? (theo’s is 55%, your realistic is 48-50%)

If YES: Move to real trading. If NO: Identify why and adjust your rules.

Step 5: Live Trading with Real Capital (Days 22-30)

Start with 1 SOL, as planned. But now you trade theo’s strategy, not theo’s account.

THEO'S STRATEGY REPLICATION:

Day 1: Watch, don't trade (confidence building)
Day 2: First 0.2 SOL trade (small)
Day 3: 0.3 SOL trade if up, 0.2 SOL if down
Day 4-7: 0.5 SOL trades, stack wins
Week 2: Scale to 0.7-1.0 SOL per trade

Rules:
├── Risk 2% per trade (your capital)
├── Hold 30-60 seconds (your speed)
├── Exit on volume drop OR price target
├── Never hold overnight
└── Record everything for analysis

Monthly Retrospective

After 30 days of trading theo’s strategy, analyze:

MONTH 1 RESULTS:

Starting capital: 1 SOL
Ending capital: 1.18 SOL
Total trades: 24
Winning trades: 11 (45.8%)
Losing trades: 13 (54.2%)
Average win: +4.2%
Average loss: -5.1%
Biggest win: +8.7%
Biggest loss: -9.2%

Expected (theo at 55%): 1.0 × 1.48 = 1.48 SOL
Actual (you at 45%): 1.18 SOL
Difference: -20% underperformance

Root causes:
├── Slower execution (30s vs 7s) → missed early exits
├── Signal timing (you entered later than theo)
├── Slippage (you got worse fills = -0.5-1% per trade)
└── Psychology (took loss too late, rode win too long)

Adjustments for Month 2:
1. Try 60-second exits instead of 30s (let winners run longer)
2. Use Photon DEX (reduce slippage by 0.3%)
3. Set hard stop-loss (-6%) to prevent catastrophic losses
4. Enter ONLY when you see theo entering (reduce false positives)

Create a Learning Page

Theo_Strategy_Journey.md

markdown

# Learning theo's Edge: Month 1 Retrospective
 
## Edge Identified
theo is a momentum scalper who:
1. Finds young tokens (5-15 min old)
2. Waits for volume/whale signal
3. Enters 2% of capital
4. Exits in 7 seconds (hard stop)
5. Captures 4-5% gains, cuts 5-6% losses
6. Achieves 55% win rate on this system
 
## Edge Replication Attempt
Adapted for human speed:
1. Find tokens on Birdeye trending
2. Wait for volume confirmation (5-min chart)
3. Enter 2% of capital
4. Exit at 60 seconds OR -6% stop loss
5. Aimed for 45%+ win rate
 
## Month 1 Results
- Win rate: 45.8% ✅ (close to target)
- Returns: +18% ✅ (profitable)
- Slippage: -0.8% ⚠️ (higher than expected)
- Accuracy: Improving (day 30 vs day 1 = +200%)
 
## Adjustments for Month 2
1. Try 90-second holds (winners run longer)
2. Photon DEX only (reduce slippage)
3. -6% hard stop (prevent -10% losses)
4. Entry only when >3 signals aligned
 
## Core Insight
theo's edge isn't magic. It's:
- Speed (you can't match, but acceptable)
- Discipline (you CAN match this)
- Signal accuracy (you can improve this with data)
- Risk management (you can copy this exactly)
 
## Can You Exceed theo's Returns?
Month 1: NO (18% vs theo's 48%)
Month 3: MAYBE (+30-40% if discipline holds)
Month 6: POSSIBLY (+50% if you add your own signals)
 
The path to exceeding theo is ADDING to his system, not replacing it.

THE COMPLETE LEARNING LOOP

MONTH 1: STUDY
├── Analyze 30 of theo's trades
├── Identify: entry, sizing, exit patterns
├── Understand: WHY each decision
└── Document: Edge Deconstruction.md

MONTH 2: REPLICATE
├── Trade theo's strategy (but at your speed)
├── Track results vs expected
├── Identify: What's working, what's not
└── Document: Strategy Replication Results.md

MONTH 3: OPTIMIZE
├── Adjust timing, signals, sizing
├── Test: Do changes improve win rate?
├── Expand: Add radiance's strategy
└── Document: Hybrid Strategy.md

MONTH 4+: INNOVATE
├── Combine theo + radiance strategies
├── Add your own signals (sentiment, macro, etc.)
├── Build: Custom system
└── Document: [Your Name]'s Trading System.md

TOOLS FOR EDGE EXTRACTION

Phase 1: Trade Collection

Solscan.io (free)
DexScreener (free)
Google Sheets (free)
Obsidian (free)

Phase 2: Pattern Recognition

Spreadsheet formulas (calculate win%, avg size, etc.)
Chart analysis (Birdeye, TradingView)
Twitter search
Manual note-taking

Phase 3: Edge Replication

Birdeye (free)
DexScreener (free)
Backpack/Phantom wallet (free)
Raydium DEX (free)
Photon (optional, $0-5/tx)

Obsidian (document learning)
Spreadsheet (track results)
Solscan (monitor performance)
Wiki updates (share insights)

WHAT YOU’LL LEARN BY MONTH 3

Understanding

✅ Why theo enters specific tokens
✅ How theo times entries (volume + whale signals)
✅ How theo manages risk (2% per trade)
✅ Why theo exits in 7 seconds
✅ How theo achieves 55% win rate

Ability

✅ Spot momentum trades independently
✅ Size positions correctly
✅ Cut losses with discipline
✅ Let winners run appropriately
✅ Achieve 45-50% win rate (human-speed)

Intuition

✅ “This token is about to pump” (pre-entry)
✅ “Now is the time to exit” (exit timing)
✅ “This signal is fake” (false positive detection)
✅ “I should sit this one out” (patience)

THE UNFAIR ADVANTAGE: DOCUMENTED LEARNING

Most traders who try to learn from theo fail because:

❌ They don’t document their learning
❌ They don’t systematize what they find
❌ They trade emotionally instead of mechanically
❌ They don’t update their wiki with findings

You have your wiki.

Every insight → Trade_Deconstruction.md Every loss → Added to Loss_Pattern_Analysis.md Every win → Added to Win_Signal_Library.md

By month 3, you’ll have the most detailed written record of how to trade like theo.

No other trader has that. That’s your edge.

SUCCESS METRICS: Month 1, 3, 6

Metric	Month 1 Target	Month 3 Target	Month 6 Target
Win Rate	45%+	50%+	55%+
Monthly Return	+15%	+25%	+40%
Avg Trade Size	2%	2.5%	3%
Biggest Loss	-9%	-8%	-6%
Avg Hold Time	60s	90s	120s
Documented Insights	50	200	500

The Real Challenge

Not learning theo’s edge. That’s months 1-2.

The real challenge: Building on theo’s edge in month 4+.

Once you’ve mastered momentum scalping, you can:

Add macro signals (Bitcoin price, Fed news)
Add sentiment analysis (Twitter momentum scores)
Add token fundamentals (creator reputation, liquidity lock)
Combine with radiance’s strategy (different tokens, different timing)

That’s where 1 SOL becomes 10 SOL.

Your Wiki Grows With Every Trade

This entire learning journey becomes 5-10 new wiki pages:

Theo_Trade_Deconstruction.md (Phase 1)
Momentum_Scalping_Framework.md (Phase 2)
Trade_Replication_Results.md (Phase 3)
Entry_Signal_Library.md (ongoing)
Exit_Strategy_Playbook.md (ongoing)
Loss_Prevention_Rules.md (ongoing)
My_Adaptation_of_Theo_Strategy.md (Phase 4)

By month 3, your wiki is a complete trading manual based on real data, real analysis, real results.

No course, no book, no mentor has that specificity.

Start Here (Tomorrow)

✅ Get theo’s wallet address
✅ Go to Solscan
✅ Find 5 of theo’s recent trades
✅ Document each one (entry, exit, PnL)
✅ Analyze the pattern (volume? price movement? timing?)
✅ Create Theo_Trade_Deconstruction_Start.md in your wiki

That’s it. That’s the first step. One hour of work.

By tomorrow night, you’ll know MORE about theo’s edge than 99% of copy traders.

By week 2, you’ll be ready to trade theo’s strategy independently.

By month 3, you’ll BE theo (or better).

farmer-detection — How to spot real traders vs farming exploits
theo — Theo’s profile and trading record
theo-style — Theo’s operational playbook for daily trading
winner-checklist — Validation framework for token entry decisions
narrative-trade — Complementary approach (narrative vs technicals)

solana memecoin wiki

Explorer

Trade Deconstruction Framework: Learn to Fish, Not Copy

Trade Deconstruction Framework: Learn to Fish, Not Copy

Executive Summary

THE PRINCIPLE: Deconstruction Over Imitation

Copy Trading (Temporary)

Trade Deconstruction (Permanent)

PHASE 1: TRADE COLLECTION (Days 1-7)

Goal

What to Capture for EACH Trade

How to Capture This Data

Step 1: Find theo’s wallet on Solscan

Step 2: Identify theo’s trades

Step 3: For each buy-sell pair, record

Step 4: Document the context

Tools Needed

Time Investment

PHASE 2: PATTERN RECOGNITION (Days 8-14)

Goal

The 5 Core Questions

Q1: ENTRY PATTERNS — How does theo find tokens?

Q2: ENTRY SIGNALS — What does theo look for at entry?

Q3: SIZING PATTERNS — How much does theo risk per trade?

Q4: EXIT PATTERNS — How does theo know when to exit?

Q5: LOSS PATTERNS — How does theo prevent cascading losses?

Deliverable: Pattern Analysis Document

PHASE 3: EDGE REPLICATION (Days 15-30)

Goal

Step 1: Identify Your Constraints vs theo

Step 2: Adapt theo’s Strategy to Your Constraints

Step 3: Build Your Own Trade Setup

Minimum Setup (Free/Low-Cost)

Step 4: Paper Trading (Days 15-21)

Step 5: Live Trading with Real Capital (Days 22-30)

PHASE 4: EDGE REFINEMENT (Month 2+)

Monthly Retrospective

Create a Learning Page

THE COMPLETE LEARNING LOOP

TOOLS FOR EDGE EXTRACTION

Phase 1: Trade Collection

Phase 2: Pattern Recognition

Phase 3: Edge Replication

Phase 4: Learning & Refinement

WHAT YOU’LL LEARN BY MONTH 3

Understanding

Ability

Intuition

THE UNFAIR ADVANTAGE: DOCUMENTED LEARNING

SUCCESS METRICS: Month 1, 3, 6

The Real Challenge

Your Wiki Grows With Every Trade

Start Here (Tomorrow)

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