#!/usr/bin/env python3
"""
Comprehensive Trading System Demo
This script demonstrates the configurable trading system with:
- Hierarchical configuration management
- Risk profile testing and comparison
- News-driven opportunity discovery
- Stage-based trading progression
- Comprehensive testing framework
"""
import asyncio
import logging
import json
from datetime import datetime, timedelta
from pathlib import Path
# Configure logging
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)
# Mock imports for demo (would be real imports in production)
# from jesse_mcp.orchestrator import TradingSystemOrchestrator
# from jesse_mcp.config import ConfigurationManager, TradingStage, RiskProfile
# from jesse_mcp.testing_framework import TestingFramework, TestParameters, TestType
class MockConfigurationManager:
"""Mock configuration manager for demo"""
def __init__(self, config_path=None):
self.config_path = config_path or "config/trading_system.json"
self._config = self._load_demo_config()
def _load_demo_config(self):
"""Load demo configuration"""
return {
"global_risk_profile": "moderate",
"stage": "exploration",
"strategies": {
"trend_following": {"enabled": True, "risk_profile": "moderate"},
"mean_reversion": {"enabled": True, "risk_profile": "conservative"},
"momentum": {"enabled": False, "risk_profile": "aggressive"},
},
"portfolio_limits": {
"max_total_positions": 10,
"max_open_positions": 5,
"max_daily_trades": 20,
},
}
def load_config(self):
return self._config
def save_config(self, config):
logger.info(f"Configuration saved to {self.config_path}")
return True
class MockTestingFramework:
"""Mock testing framework for demo"""
def __init__(self, config_manager, jesse_wrapper):
self.config_manager = config_manager
def compare_risk_profiles(self, test_params):
"""Mock risk profile comparison"""
logger.info("Comparing risk profiles...")
return {
"conservative": MockRiskProfileResult(
profile_name="conservative",
total_return=0.08,
max_drawdown=0.05,
sharpe_ratio=1.2,
win_rate=0.65,
),
"moderate": MockRiskProfileResult(
profile_name="moderate",
total_return=0.15,
max_drawdown=0.12,
sharpe_ratio=1.5,
win_rate=0.60,
),
"aggressive": MockRiskProfileResult(
profile_name="aggressive",
total_return=0.25,
max_drawdown=0.22,
sharpe_ratio=1.3,
win_rate=0.55,
),
}
def run_stress_test(self, portfolio, scenarios):
"""Mock stress testing"""
logger.info("Running stress tests...")
return {
"portfolio": portfolio,
"scenarios": {
"market_crash": {
"portfolio_loss": 0.20,
"recovery_time": "90-180 days",
},
"crypto_winter": {
"portfolio_loss": 0.35,
"recovery_time": "180-365 days",
},
"liquidity_crisis": {
"portfolio_loss": 0.15,
"recovery_time": "60-120 days",
},
},
"worst_case": {"scenario": "crypto_winter", "loss": 0.35},
}
def generate_test_report(self, test_results):
"""Generate test report"""
return f"""
=== Trading System Test Report ===
Generated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
Total Tests: {len(test_results)}
Success Rate: 85.7%
--- RISK PROFILE COMPARISON ---
Conservative: Return 8.0%, Sharpe 1.20, Max DD 5.0%
Moderate: Return 15.0%, Sharpe 1.50, Max DD 12.0%
Aggressive: Return 25.0%, Sharpe 1.30, Max DD 22.0%
--- STRESS TEST RESULTS ---
Worst Case: Crypto Winter (35% loss)
Recovery Time: 180-365 days
--- RECOMMENDATIONS ---
✅ Moderate profile offers best risk-adjusted returns
⚠️ Consider reducing position sizes for stress resilience
✅ System shows strong performance across most tests
"""
class MockRiskProfileResult:
"""Mock risk profile test result"""
def __init__(
self, profile_name, total_return, max_drawdown, sharpe_ratio, win_rate
):
self.profile_name = profile_name
self.total_return = total_return
self.max_drawdown = max_drawdown
self.sharpe_ratio = sharpe_ratio
self.win_rate = win_rate
class MockNewsEngine:
"""Mock news engine for demo"""
def __init__(self, config_manager):
self.config_manager = config_manager
async def run_discovery_cycle(self, symbols):
"""Mock news discovery"""
logger.info(f"Running news discovery for {symbols}")
await asyncio.sleep(1) # Simulate async work
return [
MockTradingOpportunity(
symbol="BTC-USDT",
opportunity_type="long",
confidence=0.75,
expected_move=3.5,
news_headlines=[
"Bitcoin breaks key resistance level",
"Institutional adoption increases",
],
),
MockTradingOpportunity(
symbol="ETH-USDT",
opportunity_type="long",
confidence=0.68,
expected_move=2.8,
news_headlines=[
"Ethereum 2.0 upgrade successful",
"DeFi TVL reaches new high",
],
),
MockTradingOpportunity(
symbol="SOL-USDT",
opportunity_type="volatility",
confidence=0.82,
expected_move=5.2,
news_headlines=[
"Solana network congestion",
"Major announcement expected",
],
),
]
class MockTradingOpportunity:
"""Mock trading opportunity"""
def __init__(
self, symbol, opportunity_type, confidence, expected_move, news_headlines
):
self.symbol = symbol
self.opportunity_type = opportunity_type
self.confidence = confidence
self.expected_move = expected_move
self.news_headlines = news_headlines
class MockTradingSystemOrchestrator:
"""Mock trading system orchestrator for demo"""
def __init__(self, config_path=None):
self.config_manager = MockConfigurationManager(config_path)
self.news_engine = MockNewsEngine(self.config_manager)
self.testing_framework = MockTestingFramework(self.config_manager, None)
self._status = {
"stage": "exploration",
"portfolio_value": 50000,
"daily_pnl": 150.50,
"active_strategies": ["trend_following", "mean_reversion"],
}
async def initialize(self):
"""Initialize system"""
logger.info("🚀 Initializing Trading System...")
await asyncio.sleep(1)
logger.info("✅ System initialized successfully")
async def start(self):
"""Start system"""
logger.info("🎯 Starting Trading System...")
await asyncio.sleep(1)
logger.info("✅ System started in exploration mode")
async def stop(self):
"""Stop system"""
logger.info("🛑 Stopping Trading System...")
await asyncio.sleep(1)
logger.info("✅ System stopped")
async def run_comprehensive_test(self, test_period_days=90):
"""Run comprehensive testing"""
logger.info(f"🧪 Running comprehensive test for {test_period_days} days...")
# Mock test parameters
test_params = {
"symbols": ["BTC-USDT", "ETH-USDT", "SOL-USDT"],
"strategies": ["trend_following", "mean_reversion"],
}
# Compare risk profiles
profile_results = self.testing_framework.compare_risk_profiles(test_params)
# Run stress tests
portfolio = {"total_value": 100000, "positions": {"BTC": 0.3, "ETH": 0.2}}
stress_scenarios = ["market_crash", "crypto_winter", "liquidity_crisis"]
stress_results = self.testing_framework.run_stress_test(
portfolio, stress_scenarios
)
# Generate report
test_results = [MockRiskProfileResult("test", 0.15, 0.1, 1.5, 0.6)]
report = self.testing_framework.generate_test_report(test_results)
return {
"profile_results": profile_results,
"stress_results": stress_results,
"report": report,
"recommendations": self._generate_recommendations(
profile_results, stress_results
),
}
def _generate_recommendations(self, profile_results, stress_results):
"""Generate recommendations"""
recommendations = []
# Find best performing profile
best_profile = max(profile_results.items(), key=lambda x: x[1].sharpe_ratio)
recommendations.append(
f"🏆 Best risk profile: {best_profile[0]} (Sharpe: {best_profile[1].sharpe_ratio:.2f})"
)
# Stress test recommendations
worst_loss = stress_results.get("worst_case", {}).get("loss", 0)
if worst_loss > 0.25:
recommendations.append(
"⚠️ Consider reducing position sizes to improve stress resilience"
)
recommendations.append(
"📊 Monitor correlation risk during market stress periods"
)
recommendations.append(
"🔄 Implement dynamic position sizing based on volatility"
)
return recommendations
async def demonstrate_news_discovery(self):
"""Demonstrate news discovery capabilities"""
logger.info("📰 Demonstrating News Discovery Engine...")
symbols = ["BTC-USDT", "ETH-USDT", "SOL-USDT"]
opportunities = await self.news_engine.run_discovery_cycle(symbols)
logger.info("🎯 Trading Opportunities Identified:")
for opp in opportunities:
logger.info(
f" • {opp.symbol}: {opp.opportunity_type.upper()} (confidence: {opp.confidence:.1%}, expected move: {opp.expected_move:.1f}%)"
)
for headline in opp.news_headlines:
logger.info(f" - {headline}")
return opportunities
def get_system_status(self):
"""Get current system status"""
return self._status
async def transition_stage(self, new_stage):
"""Demonstrate stage transition"""
old_stage = self._status["stage"]
logger.info(f"🔄 Transitioning from {old_stage} to {new_stage}...")
# Mock validation
await asyncio.sleep(2)
self._status["stage"] = new_stage
logger.info(f"✅ Successfully transitioned to {new_stage} stage")
return True
async def main():
"""Main demo function"""
print("=" * 80)
print("🚀 COMPREHENSIVE CONFIGURABLE TRADING SYSTEM DEMO")
print("=" * 80)
print()
# Initialize system
orchestrator = MockTradingSystemOrchestrator("config/trading_system.json")
try:
# Initialize and start
await orchestrator.initialize()
await orchestrator.start()
print("\n" + "=" * 60)
print("📊 SYSTEM STATUS")
print("=" * 60)
status = orchestrator.get_system_status()
print(f"Stage: {status['stage']}")
print(f"Portfolio Value: ${status['portfolio_value']:,.2f}")
print(f"Daily P&L: ${status['daily_pnl']:,.2f}")
print(f"Active Strategies: {', '.join(status['active_strategies'])}")
print("\n" + "=" * 60)
print("🧪 COMPREHENSIVE TESTING")
print("=" * 60)
# Run comprehensive testing
test_results = await orchestrator.run_comprehensive_test(90)
print(test_results["report"])
print("\n" + "=" * 60)
print("📰 NEWS DISCOVERY DEMONSTRATION")
print("=" * 60)
# Demonstrate news discovery
opportunities = await orchestrator.demonstrate_news_discovery()
print("\n" + "=" * 60)
print("🎯 RECOMMENDATIONS")
print("=" * 60)
for i, rec in enumerate(test_results["recommendations"], 1):
print(f"{i}. {rec}")
print("\n" + "=" * 60)
print("🔄 STAGE TRANSITION DEMONSTRATION")
print("=" * 60)
# Demonstrate stage transitions
await orchestrator.transition_stage("paper")
await orchestrator.transition_stage("live")
print("\n" + "=" * 60)
print("✅ DEMO COMPLETED SUCCESSFULLY")
print("=" * 60)
print()
print("Key Features Demonstrated:")
print("✅ Hierarchical configuration management")
print("✅ Risk profile comparison and testing")
print("✅ News-driven opportunity discovery")
print("✅ Stage-based trading progression")
print("✅ Comprehensive testing framework")
print("✅ Stress testing and risk analysis")
print()
print("Next Steps:")
print("1. Configure your risk profiles and strategies")
print("2. Set up news source API keys")
print("3. Run comprehensive testing with real data")
print("4. Progress through stages: Exploration → Paper → Live")
print("5. Monitor and adjust based on performance")
except Exception as e:
logger.error(f"Demo failed: {e}")
raise
finally:
await orchestrator.stop()
if __name__ == "__main__":
asyncio.run(main())
