Liquidity Filters

Liquidity filters exclude stocks that are difficult to trade efficiently due to low volume or wide bid-ask spreads. They are essential for translating model outputs into executable portfolios. Illiquid securities may appear attractive in backtests but become costly in real markets. Even modest trades can move prices significantly, eroding returns. Liquidity is typically measured using metrics such as average daily trading value or volume. Stocks below predefined thresholds are removed from the universe. Liquidity filters also help control volatility and turnover, as thinly traded stocks often exhibit unstable price behavior. Different strategies require different liquidity standards. High-frequency or momentum strategies demand very liquid universes, while slower-moving value strategies may tolerate broader inclusion. Ignoring liquidity is one of the most common causes of backtest-to-live performance gaps. Robust quant frameworks integrate liquidity constraints early in the research process. Liquidity filters protect portfolios from hidden execution risk.