Advanced Strategies
Power user configurations for sophisticated trading setups. Multi-agent portfolios, market regime detection, custom triggers, and external integrations.
Why use one agent when you can use several? Multi-agent setups let you run different strategies simultaneously, each with its own focus, risk parameters, and capital allocation.
Common Multi-Agent Architectures
| Setup | Agents | Use Case |
|---|---|---|
| Strategy Diversification | Momentum + Mean Reversion + Trend Following | Reduce correlation, smooth returns |
| Asset Specialization | BTC Agent + ETH Agent + Meme Agent | Optimize strategy per asset class |
| Timeframe Split | Scalper + Swing Trader + Position Trader | Capture opportunities across timeframes |
| Risk Tiers | Conservative + Moderate + Aggressive | Layered risk with different capital % |
| Signal + Executor | Research Agent + Trading Agent | Separate analysis from execution |
Creating Complementary Agents
Define Strategy Focus
Each agent should have a clear, distinct mandate. Overlap leads to confusion and correlated losses.
Allocate Capital
Decide how much capital each agent controls. Consider risk-weighting by strategy volatility.
Set Risk Boundaries
Each agent has its own risk parameters. Higher risk agents get smaller allocations.
Configure Coordination
Set up portfolio-level rules that prevent total exposure from exceeding limits.
When running multiple agents, you need portfolio-level coordination to prevent them from collectively exceeding your risk tolerance. COD3X provides tools for this.
Portfolio-Level Controls
| Control | What It Does | Example |
|---|---|---|
| Total Exposure Cap | Limits combined position size across all agents | Max 50% of portfolio in active positions |
| Asset Concentration Limit | Prevents over-allocation to single assets | No more than 15% in any single token |
| Correlation Awareness | Flags when agents are taking correlated positions | Alert if BTC and ETH long at same time |
| Drawdown Circuit Breaker | Pauses all agents if portfolio loss exceeds threshold | Stop trading if down 10% daily |
| Capital Rebalancing | Periodically reallocates capital based on performance | Monthly rebalance to winners |
Cross-Agent Communication
Agents can share information without directly controlling each other:
- Market regime broadcasts— One agent's regime assessment shared with others
- Position awareness — Agents know what other agents are holding
- Signal sharing — Research agent can flag opportunities for trading agents
- Risk pooling — Agents collectively respect portfolio-level limits
Markets behave differently in bull, bear, and ranging conditions. Advanced configurations let your agents detect and adapt to these regimes automatically.
Regime Types
| Regime | Characteristics | Optimal Strategies |
|---|---|---|
| Strong Uptrend | Higher highs, higher lows, positive momentum | Trend following, breakout buying, wider stops |
| Weak Uptrend | Grinding higher with frequent pullbacks | Buy dips, tighter risk, smaller positions |
| Ranging | Price consolidating between support/resistance | Mean reversion, range trading, fade extremes |
| Weak Downtrend | Lower highs, selling pressure but not panicked | Short rallies, quick exits, reduced exposure |
| Strong Downtrend | Capitulation, high volatility, continuous selling | Cash heavy, small shorts if any, patience |
| High Volatility | Large swings in both directions | Smaller positions, wider stops or stay flat |
Regime-Adaptive Behavior
You can configure different behavior for each regime:
Position Sizing
Larger in favorable regimes, smaller in hostile ones. Auto-scales based on conditions.
Strategy Selection
Different strategies activate in different regimes. Momentum in trends, mean reversion in ranges.
Risk Parameters
Tighter stops in volatile regimes, wider stops in trending markets. Dynamic adjustment.
Activity Level
More active in favorable conditions, patient or paused in hostile ones. Capital preservation first.
Beyond the standard triggers (price levels, indicators, time), power users can create complex conditional logic for when agents should act.
Trigger Types
| Trigger | Description | Example |
|---|---|---|
| Compound Conditions | Multiple conditions that must all be true | RSI < 30 AND Volume > 2x avg AND BTC above 200 MA |
| Any-Of Conditions | Any one condition being true triggers action | Price hits support OR RSI oversold OR whale accumulation |
| Sequence Triggers | Conditions that must happen in order | Break resistance THEN pullback to retest THEN bounce |
| Time-Gated Triggers | Conditions valid only during certain periods | Only enter momentum plays during US market hours |
| Cooldown Triggers | Limits frequency of specific actions | Max 1 entry per asset per 24 hours |
| External Triggers | Actions triggered by external API signals | Enter when alpha feed sends buy signal |
Trigger Chains
Chain triggers together for sophisticated setups:
Example: "Smart DCA Entry"
1. IF price drops 5% from recent high (initial trigger)
2. AND daily RSI below 40 (confirmation)
3. AND no entry in last 48 hours (cooldown)
4. THEN enter 25% of planned position
5. REPEAT at -10%, -15%, -20% with remaining capital
Connect external data sources and signal providers to your agents. Bring in alpha from anywhere and let your agent act on it.
Integration Types
Signal Providers
Connect third-party alpha sources. Agent receives signals and evaluates them against your strategy before acting.
Custom Data Feeds
Bring your own data: proprietary indicators, alternative data, custom sentiment scores.
Webhook Triggers
External systems can trigger agent actions via webhook. Integrate with TradingView alerts, custom scripts, or other platforms.
Outbound Notifications
Agent can POST to external endpoints on specific events. Build custom dashboards or connect to other systems.
Setting Up API Integration
Generate API Key
Create a unique API key in your COD3X settings. Each key can be scoped to specific agents.
Configure Endpoint
Set up your incoming webhook URL or connect to your data provider's API.
Define Signal Schema
Specify what format your signals come in and how they map to agent actions.
Set Validation Rules
Configure how the agent should validate and filter incoming signals before acting.
Beyond basic stop losses, advanced configurations provide sophisticated risk control.
| Feature | Description |
|---|---|
| Volatility-Adjusted Sizing | Position sizes scale inversely with current volatility |
| Correlation-Aware Limits | Reduces exposure when holding correlated assets |
| Time-Decay Stops | Stops tighten as trade duration increases |
| Equity Curve Trading | Reduces risk when recent performance is poor |
| Heat Maps | Visual representation of portfolio risk distribution |
| Scenario Analysis | What-if modeling for extreme market moves |
Before deploying advanced configurations with real capital, validate them thoroughly.
Validation Pipeline
Backtest
Run your strategy against historical data. Identify weaknesses and optimize parameters.
Paper Trade
Deploy in simulation mode with live market data. Verify real-time behavior without risk.
Small Live Test
Deploy with minimal capital. Confirm production behavior matches expectations.
Scale Up
Gradually increase capital as confidence grows. Monitor for regime changes.