LIVE Real-Time Trading Systems
Live trading is a fundamentally different challenge — and it will humble you
Learning Objectives
- •Design event-driven trading systems
- •Handle real-time data feeds and order management
- •Understand latency requirements for different strategies
Explain Like I'm 5
A live trading system is fundamentally different from a backtest. In a backtest, you process historical data sequentially — nice and calm. In live? Data arrives unpredictably. New bars drop. Ticks stream in. Orders fill (or don't). Connections die. Your system must react to EVENTS as they happen, handle errors without crashing, and never miss a signal. The first time you run a live system and watch it make real decisions with real money, it's a qualitatively different experience.
Think of It This Way
A backtest is like watching a recorded game and calling plays from your couch. Easy — you can pause, rewind, take your time. Live trading is like actually playing the game in real-time with real consequences. You must make instant decisions, handle unexpected situations, and there's no pause button.
1Event-Driven Architecture
2Error Handling — Things WILL Go Wrong
3State Management — The Hidden Complexity
4The Shadow Trading Pattern
Shadow Trading Timeline: Confidence Building
5Graceful Shutdown
Hands-On Code
Event-Driven Trading Loop
import time
import logging
logger = logging.getLogger('v7_live')
class LiveTradingLoop:
"""Main live trading loop with error handling."""
def __init__(self, engine, connector, bar_interval_sec=900):
self.engine = engine
self.connector = connector
self.interval = bar_interval_sec
self.running = False
def start(self):
self.running = True
logger.info("V7 Live Trading STARTED")
while self.running:
try:
cycle_start = time.time()
# 1. Check connection
if not self.connector.is_connected():
logger.warning("Connection lost, reconnecting...")
self.connector.connect()
continue
# 2. Process signals
signals = self.engine.scan_all_symbols()
for signal in signals:
# 3. Risk check
if not self.engine.risk_check(signal):
logger.info(f"SKIP {signal['symbol']}: risk limit")
continue
# 4. Execute
result = self.connector.place_order(
symbol=signal['symbol'],
direction=signal['direction'],
volume=signal['volume'],
sl=signal['sl'],
tp=signal['tp'],
)
logger.info(f"ORDER: {result}")
# 5. Update existing positions
self.engine.update_exits()
# 6. Log state
self.engine.log_state()
# 7. Sleep until next bar
elapsed = time.time() - cycle_start
sleep_time = max(0, self.interval - elapsed)
time.sleep(sleep_time)
except KeyboardInterrupt:
self.running = False
logger.info("Manual stop requested")
except Exception as e:
logger.error(f"Error in trading loop: {e}", exc_info=True)
time.sleep(60) # wait before retryingThe live loop must handle EVERYTHING: connection issues, data errors, order rejections, and crashes. The golden rule: when in doubt, do nothing. Missing a trade is better than a bad trade. The best live trading systems are 80% error handling and 20% actual trading logic.
Knowledge Check
Q1.Your live trading system loses connection to the broker. What should happen to existing positions?
Assignment
Implement a basic event-driven trading loop with: connection monitoring, error handling, logging, and graceful shutdown. Test it by simulating connection drops and data errors.