Slippage Modeling

Slippage modeling estimates the difference between theoretical trade prices and actual execution prices. It accounts for bid-ask spreads, market impact, and timing delays. Backtests that ignore slippage often overstate returns. Slippage modeling introduces realistic cost assumptions so simulated performance better reflects live conditions. Slippage depends on trade size, liquidity, volatility, and market environment. Larger trades in less liquid stocks typically experience higher slippage. Quant strategies incorporate slippage through fixed cost assumptions, percentage-based estimates, or volume-sensitive models. Advanced frameworks dynamically adjust slippage based on market conditions. Accurate slippage modeling is critical for evaluating turnover-heavy strategies like Momentum. Without it, apparent alpha may vanish after costs. Slippage modeling bridges the gap between research and reality.