Co-location vs Cloud Trading: Infrastructure Guide

Your trading infrastructure determines your competitive advantage. Co-location offers microsecond latency but costs lakhs monthly. Cloud provides flexibility at millisecond speeds for fraction of cost.

This guide helps you choose the right infrastructure for your strategy, capital, and technical capabilities.

Infrastructure Comparison

Latency Benchmarks

Setup	Latency	Cost/Month	Best For
Co-location (NSE)	50-200μs	₹5-10L	HFT, Market Making
Cloud (AWS Mumbai)	5-15ms	₹50-100K	Low-freq algo, Retail
VPS (Indian DC)	10-30ms	₹5-20K	Medium-freq strategies
Home Internet	50-200ms	₹1-2K	Long-term, Manual

When Co-location Makes Sense

✅ Strategy PnL > ₹50L/year ✅ Latency-sensitive (HFT, arbitrage) ✅ High trade frequency (>1000/day) ✅ Professional team with ops capability

❌ Low-frequency strategies ❌ Limited capital (<₹50L) ❌ Solo traders without ops expertise

class InfrastructurePlanner:
    """
    Calculate infrastructure ROI
    """
    
    def __init__(self, strategy_params: dict):
        self.params = strategy_params
    
    def calculate_roi(self, infrastructure: str) -> dict:
        """Calculate ROI for infrastructure choice"""
        costs = {
            'co_location': 600000,  # ₹6L/year
            'cloud': 60000,         # ₹60K/year
            'vps': 120000          # ₹12K/year
        }
        
        latencies = {
            'co_location': 0.0002,   # 200μs
            'cloud': 0.010,          # 10ms
            'vps': 0.020            # 20ms
        }
        
        # Estimate alpha decay from latency
        baseline_alpha = self.params['baseline_alpha']
        latency = latencies[infrastructure]
        
        # HFT strategies lose ~10% alpha per millisecond delay
        if self.params['strategy_type'] == 'hft':
            alpha_loss = latency * 1000 * 0.10
        else:
            alpha_loss = latency * 100 * 0.01  # Low-freq less sensitive
        
        realized_alpha = baseline_alpha * (1 - alpha_loss)
        annual_pnl = realized_alpha * self.params['capital']
        net_pnl = annual_pnl - costs[infrastructure]
        
        return {
            'infrastructure': infrastructure,
            'cost': costs[infrastructure],
            'realized_alpha': realized_alpha,
            'annual_pnl': annual_pnl,
            'net_pnl': net_pnl,
            'roi': net_pnl / costs[infrastructure]
        }

planner = InfrastructurePlanner({
    'baseline_alpha': 0.15,
    'capital': 5000000,
    'strategy_type': 'medium_freq'
})

for infra in ['co_location', 'cloud', 'vps']:
    result = planner.calculate_roi(infra)
    print(f"{infra}: Net PnL ₹{result['net_pnl']:,.0f}, ROI {result['roi']:.1f}x")