With regards to futures contracts as well as other financial instruments, slippage is the difference between estimated transaction costs and the amount actually paid. Brokers may not always be effective enough at executing orders. Market-impacted, liquidity, and frictional costs may also contribute. Algorithmic trading is often used to reduce slippage.
Using initial mid price
Nassim Nicholas Taleb (1997) defines slippage as the difference between the average execution price and the initial midpoint of the bid and the offer for a given quantity to be executed.
Using initial execution price
Knight and Satchell mention a flow trader needs to consider the effect of executing a large order on the market and to adjust the bid-ask spread accordingly. They calculate the liquidity cost as the difference of the execution price and the initial execution price.
Victor Niederhoffer says: "In statistical terms, I figure I have traded about 2 million contracts, with an average profit of $70 per contract (after slippage of perhaps $20). This average is approximately 700 standard deviations away from randomness".
Reverse slippage as described by Taleb occurs when the purchase of a large position is done at increasing prices, so that the mark to market value of the position increases. The danger occurs when the trader attempts to exit his position. If the trader manages to create a squeeze large enough then this phenomenon can be profitable.
A portfolio of securities that is leveraged with borrowed funds will encounter the slippage that comes with how the portfolio increase/decrease multiply.