Skip to content

Operating Model

Overview

The Edge Factory operates as a continuous pipeline: Research → Validate → Deploy → Monitor → Retire.

┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│  RESEARCH   │───▶│  VALIDATE   │───▶│   DEPLOY    │───▶│   MONITOR   │───▶│   RETIRE    │
│  (Ideas)    │    │  (Backtest) │    │  (Paper→Live)│   │  (Track)    │    │  (Sunset)   │
└─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘
      │                  │                  │                  │                  │
      ▼                  ▼                  ▼                  ▼                  ▼
   Hypothesis        Pass/Fail          Staged            Drift Alert        Archive +
   Generation        Gates              Rollout           Response           Post-mortem

Stage Gates

Gate 1: Research → Validation

Criterion Pass Fail
Hypothesis documented Written rationale exists No documentation
Data requirements defined Sources + frequency specified Unclear data needs
Initial signal logic Pseudocode or prototype Vague concept only

Gate 2: Validation → Deployment

Criterion Pass Fail
In-sample Sharpe ≥ 1.2 < 1.2
Out-of-sample Sharpe ≥ 0.8 < 0.8
OOS degradation < 30% ≥ 30%
Walk-forward consistency 60%+ windows profitable < 60%
Max drawdown (backtest) < 8% ≥ 8%
Anti-bias audit All tests pass Any test fails
Independent review Approved Rejected

Gate 3: Deployment Stages

Stage Duration Criteria to Advance
Paper trading 2-4 weeks min Matches backtest within 20%
Live (minimal size) 2-4 weeks No execution issues, stable P&L
Live (target size) Ongoing Continuous monitoring

Gate 4: Monitoring → Retire

Trigger Action
Drawdown > 50% of max allowed Pause strategy, investigate
30-day Sharpe < 0.5 Flag for review
60-day Sharpe < 0.3 Mandatory review meeting
90-day cumulative loss Retire strategy
Regime shift detected Reduce size, investigate

Roles and Responsibilities

Role Responsibility Current Assignment
Strategy Researcher Generate hypotheses, prototype signals Founder + Claude agents
Quant Engineer Implement backtests, feature engineering Founder + Claude agents
Risk Manager Set limits, monitor exposure, approve deployments Founder
Auditor Independent validation, adversarial testing Claude audit agent
Operator Execute deployments, incident response Founder

Toolchain

Function Tool Notes
Strategy development Pine Script v6 TradingView indicators/strategies
Backtesting Python (vectorbt/backtrader) Local execution
Live signals TradingView alerts → Webhook JSON format
Execution (FX) MT5 Via MQL5 or API bridge
Execution (Crypto) Exchange APIs Binance, Bybit, etc.
Paper trading TradingView Paper Or broker demo accounts
Monitoring Custom dashboards Metrics collection TBD
Version control Git All code and configs
Documentation Markdown in repo Single source of truth

Workflow Cadence

Activity Frequency Owner
Strategy review Weekly Founder
Risk limit check Daily (automated) Monitoring system
Backtest refresh Monthly or on data update Quant pipeline
Full audit Per strategy, pre-deployment Audit agent
Post-mortem (retired strategies) Within 1 week of retirement Founder

Communication

  • Alerts: Webhook → Discord/Telegram for trade signals
  • Incidents: Logged in docs/runbooks/incident_log.md
  • Decisions: Logged in research/reports/ with rationale

Constraints

  1. No manual overrides in live trading: System trades as programmed or not at all
  2. All changes via version control: No direct edits to live configs
  3. Staged rollouts only: Never deploy directly to full live size
  4. Document before deploy: No undocumented strategies go live