What is Slippage?

Slippage is the difference between the expected price of an order and the actual execution price. It occurs when the market moves between the time an order is submitted and when it is filled, resulting in execution at a different price than intended. Slippage most commonly happens with market orders, stop orders (which become market orders when triggered), and during fast-moving markets or periods of low liquidity. Slippage is not always negative. Positive slippage occurs when you get a better price than expected (buying lower or selling higher). Negative slippage occurs when you get a worse price (buying higher or selling lower). In practice, negative slippage is more common because prices tend to move against you during the milliseconds between order submission and execution, especially during volatile periods. For most retail traders, slippage adds 0.5-2 pips (forex) or 1-2 ticks (futures) of additional cost per trade.

• The difference between expected execution price and actual execution price
• Most common with market orders and stop orders during fast markets
• Can be positive (favorable) or negative (unfavorable)
• Negative slippage is more common in practice
• Increases during low liquidity, high volatility, and news events

Slippage occurs for several reasons. First, market orders are filled at the best available price, which may differ from the last quoted price if the market has moved during order transmission. In electronic markets, this latency is measured in milliseconds, but during fast moves, prices can change significantly in that time. Second, stop loss orders become market orders when the stop price is hit. If the market gaps past your stop price (common during news events or overnight gaps), the order fills at the next available price, which may be well beyond your stop. Third, large orders may not have enough liquidity at a single price level to fill completely. The order fills partially at the intended price and partially at progressively worse prices (this is called market impact). Fourth, during extreme events (flash crashes, breaking news), liquidity can temporarily disappear, causing massive slippage on all order types.

Slippage on stop losses is particularly important for risk management because it means your actual loss can exceed the planned loss. If your stop loss is at $47.00 but slippage fills you at $46.80, you lose an extra $0.20 per share. On 500 shares, that is an extra $100 beyond your planned risk. During major news events, stop loss slippage can be extreme. During the Swiss National Bank (SNB) event in January 2015, some forex traders experienced slippage of 1,000+ pips on their EUR/CHF stop losses as the market gapped through all pending orders. While such extreme events are rare, they illustrate why stop losses do not guarantee a maximum loss; they guarantee execution but not price. To account for slippage in your risk management, add a slippage estimate to your stop loss distance when calculating position size. For futures, add 1-2 ticks per side. For forex, add 0.5-1 pip per side. This ensures that even with typical slippage, your actual loss stays close to your target risk.

While slippage cannot be eliminated entirely, several practices can reduce it. Trade during high-liquidity sessions (London/New York overlap for forex, regular trading hours for futures and stocks) when the order book is deep and spreads are tight. Use limit orders instead of market orders when possible: limit orders guarantee price but not execution, so you may miss a fill, but you will never get a worse price. Avoid trading during major news events unless your strategy specifically requires it. Keep position sizes reasonable relative to the instrument's typical volume to avoid market impact. Choose a broker with fast execution speeds and direct market access (DMA/ECN). In futures, consider using limit orders at your stop level rather than stop market orders for entries (though for stop losses, market orders are generally safer because execution is guaranteed).

• Trade during high-liquidity sessions (London/New York overlap)
• Use limit orders when possible for entries
• Avoid trading during major news events
• Keep position sizes proportional to market volume
• Choose a broker with fast execution and low latency
• For exits, use stop market orders to guarantee execution

Tracking slippage over time provides actionable data for optimizing your trading execution. To measure slippage on each trade, record the intended entry price and the actual fill price. The difference is your slippage: if you intended to buy at 1.10500 and were filled at 1.10508, you experienced 0.8 pips of negative slippage. Similarly, record the intended exit price and the actual exit fill. Over 100+ trades, calculate your average slippage per trade, separating it by order type (market orders, stop orders, limit orders), by session (London, New York, Asian), and by market condition (normal, news, low liquidity). Most traders who track slippage discover patterns they can exploit. Common findings include: market order slippage is 2-3x higher during the first 15 minutes of a session opening, slippage on stop orders is significantly higher during NFP and FOMC announcements, and certain brokers consistently provide better fills than others for the same instruments. Once you have this data, you can make informed decisions about order timing, broker selection, and which trading sessions to focus on. A practical framework for slippage tracking is to maintain a simple spreadsheet with columns for trade date, instrument, order type, intended price, actual fill price, slippage in pips, and market condition. Aggregate this data monthly and look for trends. If your average slippage is increasing over time, investigate whether market conditions have changed or if your broker's execution quality has deteriorated. Professional traders review slippage data quarterly and use it as a factor in broker evaluations and strategy refinements.

Automated trading systems (expert advisors, NinjaScript strategies, algorithms) face unique slippage challenges that differ from manual trading. In automated trading, the execution speed is determined by the connection latency between your platform and the broker's server, the broker's internal execution speed, and the speed at which the market is moving. Co-location (placing your server physically close to the exchange's matching engine) can reduce latency to under 1 millisecond, but this is typically only available to institutional traders. Retail algorithmic traders using platforms like NinjaTrader typically experience 50-500 milliseconds of latency, during which the price can move. For a strategy that generates market orders at the close of each bar (a common approach), the slippage depends on the bar timeframe. On a 1-minute chart, the price is unlikely to move significantly in 100 milliseconds. On a tick chart during fast markets, even 100 milliseconds of latency can result in substantial slippage. Backtesting automated strategies with zero slippage produces dangerously misleading results. A strategy that shows a 2.0 profit factor with zero slippage might show only 1.3 with 1-tick slippage per side, or even become unprofitable with 2 ticks of slippage. The general rule for automated strategy backtesting is to add at least 1 tick of slippage per side for futures and 0.5-1 pip per side for forex. If the strategy remains profitable with 2x your expected slippage, it is robust enough to deploy. One advantage of automated trading is consistency: while a manual trader's slippage varies with their reaction time and emotional state, an algorithm submits orders at the same speed every time. This consistency makes slippage more predictable and easier to account for in backtesting.

• Automated systems experience slippage from connection latency (50-500ms for retail)
• Always backtest with at least 1 tick or 0.5-1 pip of slippage per side
• Test profitability at 2x expected slippage for robustness verification
• Co-location reduces latency but is typically only available to institutions
• Automated trading has more consistent (predictable) slippage than manual trading
• Bar-close execution on fast charts is more susceptible to slippage than on slower timeframes

Slippage is often the most underestimated trading cost because, unlike commissions and spreads, it is not displayed on any invoice or account statement. Yet for active traders, slippage can rival or exceed commission costs. Consider a day trader taking 8 trades per day on the E-mini S&P 500 (ES) with average slippage of 1 tick ($12.50) per round trip. Over 20 trading days per month: 8 x 20 x $12.50 = $2,000 per month in slippage costs. Over a year, that is $24,000. For a $50,000 account, slippage alone consumes 48% of the account annually before any other costs or profits. Even for a less active trader taking 2 trades per day on forex with mini lots and 0.5 pips of average slippage ($0.50 per trade): 2 x 20 x $0.50 = $20 per month, or $240 per year. While this seems modest, for a $5,000 account it represents 4.8% of capital consumed by slippage. The cumulative nature of slippage makes it particularly damaging to strategies with thin edges. A strategy with a per-trade expectancy of $15 that experiences $5 of slippage per trade loses 33% of its edge to an invisible cost. The same strategy with $10 of slippage per trade retains only $5 of expectancy — a 67% reduction. This explains why many strategies that look promising in zero-slippage backtests fail in live trading: the edge was consumed by slippage that was not accounted for. To quantify your annual slippage impact, multiply your average slippage per trade (in dollars) by your annual trade count. If this number exceeds 10% of your expected annual gross profit, you should actively work to reduce slippage through better execution practices, broker selection, or reduced trade frequency.