Algorithmic Strategy Design: From Idea to Execution

Module: Fintech AI | Difficulty: Advanced

Strategy Lifecycle

1. Research → 2. Backtest → 3. Paper Trade → 4. Live Trade → 5. Monitor

Risk Controls

Live Monitoring

class AlgoStrategy:
    def __init__(self, risk_limits):
        self.limits = risk_limits; self.positions = {}
    def check_risk(self, order):
        if abs(order['size']) > self.limits['max_position']:
            return False
        if self.daily_pnl < -self.limits['max_daily_loss']:
            return False
        return True
    def execute(self, signal, market_data):
        if self.check_risk(signal):
            order = self.generate_order(signal, market_data)
            return self.submit_order(order)
        return None

Research Insight: The gap between backtest and live performance is the biggest challenge in algorithmic trading. Typical degradation is 50-70%. Key causes: market impact, latency, slippage, and regime changes. Paper trading helps quantify this degradation before risking capital.