Using Order Book Slippage to Assess Crypto Liquidity and Volatility
Summary
The article explains order book slippage as the extra execution cost incurred when a market order consumes liquidity beyond the best available price. It advocates calculating slippage from the quantities available at each price level, which reflects the actual size filled more directly than an unweighted average price. The discussion applies the measure to large ETH/USDT orders on Binance and compares buy and sell slippage over time with volume and volatility measures.
The analysis reports that slippage is higher during weekdays, particularly around US market hours, and that it correlates more strongly with historical and implied volatility than with trading volume. It also observes that low-slippage periods coincided with ETH rallies in the sample, while high-slippage periods often aligned with troughs. These are visual and regression-based associations, not proof that slippage predicts returns or causes price moves. The sample is limited to one pair and venue, and the article’s historical patterns need validation before use elsewhere.
Key ideas
- Slippage measures execution cost beyond the best quoted price when an order exceeds available top-of-book liquidity.
- A quantity-based calculation accounts for the amounts filled at successive order book price levels.
- In the analyzed ETH/USDT data, slippage was positively associated with historical and implied volatility.
- The reported association between slippage and price movements does not establish predictive power or causation.
- The findings come from a specific pair, exchange, and historical sample and may not generalize.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.