Trading Lab Execution Plan - Work Tick 2026-02-26

Run ID: run_dispatch_20260226_2345_run_57d6f4756272
Focus: Execution-truth builds + replay/live validation + journaling artifacts
Risk Tier: SAFE
Status: Planning Phase - No Trading Signals/Advice

Overview

This document outlines the complete execution plan for 6 trading lab tasks, focusing on engineering processes, test frameworks, and validation pipelines. All work is experimental and requires thorough testing before any live deployment.

Task Breakdown & Execution Plan

TRADING D: EA Execution Plan (MT5) + Test Environment

Objective: Define alert-to-order mapping with comprehensive testing framework

Alert-to-MT5 Order Mapping:

Alert Reception Pipeline:
1. Webhook receives structured JSON payload
2. Validation layer (schema, rate limits, authentication)
3. Risk module evaluation (position sizing, exposure limits)
4. Symbol mapping & market hours check
5. MT5 order placement via MQL5 API
6. Execution confirmation & logging

Risk Module Specifications:

Maximum daily trades per symbol: 10
Maximum portfolio exposure: 2% per position
Drawdown circuit breaker: 5% daily loss
Time-based filters: Respect market sessions
Position size calculator: ATR-based or fixed percentage

Test Environment Checklist:

Demo MT5 account setup with test broker
MQL5 EA framework with logging
Mock webhook server for alert simulation
Backtesting environment with historical tick data
Risk module unit tests
Order execution latency measurement tools
Error handling & recovery procedures
Performance monitoring dashboard

Machine Requirements:

Dedicated Windows VPS for MT5 stability
Backup connection for redundancy
Real-time logging to external database
Alert notification system for failures

TRADING C: Alerts Spec + Webhook Payload (Automation)

Alert Conditions Schema:

{
  "timestamp": "2026-02-26T23:45:00Z",
  "symbol": "EURUSD",
  "action": "BUY|SELL|CLOSE",
  "signal_strength": 0.75,
  "entry_price": 1.0850,
  "stop_loss": 1.0800,
  "take_profit": 1.0950,
  "risk_percent": 1.0,
  "session": "LONDON|NY|ASIAN",
  "timeframe": "M15",
  "reason_codes": ["RSI_OVERSOLD", "SUPPORT_BOUNCE"],
  "confidence": "HIGH|MEDIUM|LOW"
}

Webhook Payload Guardrails:

Rate limiting: Maximum 50 alerts per hour
Session filters: Only trade during specified market hours
Cooldown periods: 15-minute minimum between signals for same symbol
Duplicate prevention: Alert ID tracking
Validation rules: Price within 1% of current market
Emergency stop: Manual override capability

Security Measures:

API key authentication
IP whitelist restrictions
Payload encryption (HTTPS only)
Request signing for integrity
Audit trail logging

TRADING B: Strategy Backtest Pass (Baseline) + Metrics

Backtest Framework:

Historical data: 2-year dataset minimum
Tick-level precision for entry/exit accuracy
Realistic spread and commission modeling
Slippage simulation based on volatility

Core Metrics Definition:

Performance Metrics:
- Profit Factor (PF): Target > 1.3
- Maximum Drawdown (DD): Target < 15%
- Win Rate: Target 45-65% (avoid overfitting)
- Average Win/Loss Ratio: Target > 1.2
- Sharpe Ratio: Target > 1.0
- Total Trades: Minimum 100 for statistical significance

Session-Based Analysis:
- London Session (08:00-17:00 GMT)
- New York Session (13:00-22:00 GMT)  
- Asian Session (00:00-09:00 GMT)
- Session overlap periods

Anti-Overfitting Measures:

Out-of-sample testing (30% holdout)
Walk-forward optimization
Parameter robustness testing
Monte Carlo simulation
Cross-validation across different market conditions

"Good" Metrics Thresholds:

Minimum trade sample: 100 trades
Maximum consecutive losses: 8
Recovery time from DD: < 30 trading days
Consistency check: Positive performance across quarters

TRADING A: Finalize Indicator Rules + Visuals (V2.6)

Indicator Validation Checklist:

No repainting behavior confirmed
Signal generation logic documented
Entry/exit rules clearly defined
Visual elements optimized for clarity
Performance impact assessment
Multi-timeframe compatibility tested

Session & Filter Configuration:

// Session Management
london_session = time(timeframe.period, "0800-1700", "GMT")
ny_session = time(timeframe.period, "1300-2200", "GMT")
asian_session = time(timeframe.period, "0000-0900", "GMT")

// Filters
volatility_filter = atr(14) > atr(50) * 1.2
trend_filter = ema(21) > ema(50)
volume_filter = volume > sma(volume, 20) * 1.1

Signal Verification:

Backtest against known market events
Paper trading validation period
Signal-to-noise ratio optimization
False signal reduction techniques

Indicator V2.7: HUD Score + Reason Codes + Counters + JSON Alerts

Enhanced Features Specification:

HUD Scoring System:

Score Calculation:
- Technical confluence (0-40 points)
- Market structure (0-30 points)
- Volume confirmation (0-20 points)  
- Session timing (0-10 points)

Grade Assignment:
- A+ (90-100): Exceptional setup
- A  (80-89): Strong signal
- B  (70-79): Moderate confidence
- C  (60-69): Weak signal
- F  (<60): No trade

Reason Codes Framework:

PASS Reasons:
- TREND_ALIGNED: Price follows primary trend
- SUPPORT_BOUNCE: Clear support level reaction
- RSI_OVERSOLD: RSI < 30 with divergence
- VOLUME_CONFIRM: Above-average volume spike
- SESSION_OPTIMAL: Trading during high-liquidity hours

BLOCK Reasons:
- NEWS_RISK: High-impact news within 1 hour
- LOW_VOLATILITY: ATR below threshold
- CHOPPY_MARKET: Sideways price action detected
- SESSION_END: Approaching session close
- MAX_EXPOSURE: Risk limits reached

Win/Loss Counter Implementation:

// Per symbol/timeframe tracking
var int wins = 0
var int losses = 0
var float win_rate = 0.0
var string performance_grade = ""

// Update counters on trade close
if strategy.closedtrades.exit_time(strategy.closedtrades - 1) == time
    if strategy.closedtrades.profit(strategy.closedtrades - 1) > 0
        wins := wins + 1
    else
        losses := losses + 1
    
    win_rate := wins / (wins + losses) * 100

JSON Alert Structure:

{
  "indicator": "UI_Clarity_V2.7",
  "timestamp": "{{time}}",
  "symbol": "{{ticker}}",
  "timeframe": "{{interval}}",
  "action": "{{strategy.order.action}}",
  "score": 85,
  "grade": "A",
  "entry_price": "{{close}}",
  "stop_loss": "{{strategy.order.stop}}",
  "take_profit": "{{strategy.order.limit}}",
  "risk_percent": 1.5,
  "reason_codes": ["TREND_ALIGNED", "VOLUME_CONFIRM"],
  "session": "LONDON",
  "win_rate": 67.3,
  "total_trades": 156,
  "performance_stats": {
    "wins": 105,
    "losses": 51,
    "avg_win": 1.2,
    "avg_loss": -0.8
  }
}

Default Settings:

Confirm-on-close: ENABLED (prevents false signals)
Alert frequency: Once per bar close
Risk per trade: 1.0%
Maximum daily alerts: 10 per symbol

Indicator V2.7: Shipping & Testing Checklist

File Delivery Package:

/second-brain/brain/tradingview/v2.7/
├── UI_Clarity_V2.7_Indicator.pine
├── UI_Clarity_V2.7_Strategy.pine
├── Installation_Guide.md
├── Settings_Recommended.json
├── Testing_Checklist.md
└── Demo_Screenshots/

Installation Instructions:

Open TradingView Pine Editor
Create new indicator script
Paste UI_Clarity_V2.7_Indicator.pine content
Save as "UI Clarity V2.7"
Apply to chart with recommended settings
Configure alerts using JSON template
Test on demo account for 1 week minimum

Recommended Demo Settings:

Risk per trade: 0.1% (ultra-conservative for demo)
Maximum positions: 3 concurrent
Trading sessions: London + NY overlap only
Minimum score threshold: 80 (A grade)
Stop loss: 1.5x ATR
Take profit: 2.5x ATR

Pre-Release Testing Protocol:

No-repaint verification across 100+ bars
Alert accuracy testing (manual vs automated)
Performance impact measurement
Multi-symbol compatibility test
Edge case handling (gaps, low volume)
JSON payload validation
Integration with webhook receiver
Demo account execution test

Implementation Timeline

Week 1: Tasks A & B (Finalize V2.6, Baseline Backtest) Week 2: Tasks C & D (Alerts System, EA Framework)
Week 3: Task 5 (V2.7 Development & Testing) Week 4: Task 6 (Documentation & Demo Preparation)

Risk Management & Compliance

Engineering Safeguards:

All testing on demo accounts only
Manual approval required for live deployment
Kill switch for emergency stop
Real-time monitoring and alerting
Audit trail for all actions
Regular backup and recovery testing

Documentation Requirements:

Test results documented and archived
Code review process for all changes
Change log maintenance
Performance baseline establishment
Risk assessment documentation

Validation Gates:

Code review and unit testing
Demo account validation (minimum 2 weeks)
Performance metrics verification
Risk management approval
Final documentation review
Go/No-go decision point

Deliverables Summary

This execution plan provides comprehensive specifications for:

Robust alert-to-execution pipeline with safeguards
Professional backtesting framework with anti-overfitting measures
Enhanced indicator with scoring, reasoning, and tracking
Complete testing and validation protocols
Documentation and deployment procedures

All components focus on engineering excellence, risk management, and systematic validation before any live deployment consideration.

IMPORTANT: This is an experimental framework. No live trading should occur without extensive testing, validation, and appropriate risk management oversight. All work remains in development/testing phase until explicit approval for live deployment.

Run Dispatch 20260226 2345 Run 57d6f4756272