Trading System Architecture: Low-Latency and High-Throughput

Module: Fintech AI | Difficulty: Advanced

System Architecture

Order Management

High Availability

class TradingSystem:
    def __init__(self, exchange连接, risk_engine):
        self.exchange = exchange连接
        self.risk = risk_engine; self.positions = {}
    def on_market_data(self, data):
        signal = self.strategy(data)
        if signal:
            order = self.create_order(signal)
            if self.risk.check(order):
                self.exchange.submit(order)
    def create_order(self, signal):
        return {
            'symbol': signal['symbol'],
            'side': signal['side'],
            'size': signal['size'],
            'type': 'limit',
            'price': signal['price']
        }

Research Insight: Trading system architecture requires balancing latency, throughput, and reliability. The lowest latency systems use FPGAs for market data processing and custom ASICs for order routing. However, most strategies don't need ultra-low latency — the key is matching system architecture to strategy requirements.