What Is Slippage?

Slippage is the reason a strategy can be profitable in a backtest and unprofitable in an account, and it is measured far less often than it is discussed.

The four sources

The spread. The gap between bid and ask. A market buy pays the ask and a market sell receives the bid, so the round trip costs the spread even if the price never moves. This is not really slippage in the strict sense but it is the largest component of real execution cost for most retail strategies.

Latency. Time passes between the decision and the order reaching the market. In a moving market the price at arrival is not the price at decision. For a copied trade, that gap includes the entire replication pipeline.

Market impact. An order larger than the size resting at the best price consumes it and fills progressively worse against deeper levels. Your own order moved the price against you.

Gaps. The price can move from above your level to below it without trading in between — over a weekend, through a news release, or on a reopen after a halt. Stops are particularly exposed here, because the order is sent when the level is reached and fills at whatever exists.

Where it is worst

Slippage is not uniformly distributed, and knowing where it concentrates is more useful than a general estimate.

Short-dated out-of-the-money options late in the session. Near-the-money strikes on major index products trade penny-wide for much of the day, so options are not uniformly illiquid. The deterioration is specific: out-of-the-money short-dated strikes widen through the session, and the final thirty minutes are worst as market makers unwind hedges. A spread that was a few cents at the open can be ten times that by mid-afternoon.

Overnight futures. Volume concentrates in the US cash session. The same order in the overnight leg meets a thinner book, so a strategy validated on regular-hours data pays more than it modelled when it runs continuously.

Around scheduled events. Economic releases and earnings produce fast moves and temporarily wider spreads, which is when many strategies are most active.

When many participants act at once. Copied trades are the clearest case — a group of followers replicating one signal competes for the same liquidity, and the provider traded against an untouched book while followers trade against one their peers are consuming.

Why backtests understate it

Systematically, not occasionally.

A backtest fills at a price from historical data — often the close, sometimes a modelled mid. Neither is an execution. There was no spread crossed, no queue joined, and no liquidity consumed.

Adding a fixed slippage assumption helps and is still a simplification, because real slippage varies with volatility, time of day, and order size, and it is largest precisely in the conditions that produce a strategy's biggest moves. A constant assumption is most wrong when it matters most.

The practical consequence is that a strategy whose edge is thinner than its true execution cost looks profitable historically and is not. High-frequency strategies are the most exposed, because the cost applies per trade while the edge per trade is small.

Measuring your own

The step almost nobody takes, and the only one that answers the question for your account.

Log the price your system decided at and the price it filled at, on every trade. The difference is your slippage, and it is a number rather than an assumption.

Then look at its distribution rather than its average. Slippage is usually skewed — mostly small with occasional large values — and the large values arrive in the fast conditions that also produce your largest position moves. An average conceals that.

Break it out by time of day and by instrument. The result is often that a strategy is profitable in some hours and not others, which is directly actionable in a way that an aggregate figure is not.

What reduces it

Not eliminated, bounded.

Limit orders instead of market orders trade fill certainty for price certainty. You will not fill worse than your limit, and you may not fill at all — which on an exit is a worse problem than the slippage.

Trading liquid instruments and liquid hours. The most effective single change for most retail strategies, and the least popular because it removes trades.

Smaller orders relative to the book reduce market impact, though on options the indivisibility of contracts limits how far this goes.

Price tolerance thresholds that skip a trade when the market has moved beyond a set distance from the expected price. This converts a bad fill into a missed trade, which is generally the better failure.

Keeping slow work off the order path. Authentication, symbol resolution, and analytics all add latency if they happen between decision and submission. Holding a warm session and doing computation on worker thread pools keeps the submission path short.

Fewer intermediary hops. Every relay between your decision and your broker is latency. Running the client close to the broker connection in a self-hosted environment removes hops a third-party service adds.

The honest limits

Slippage cannot be engineered to zero. Some component of it is the market charging you for immediacy, and immediacy is what an order is asking for.

Reducing it usually costs something else — limit orders risk no fill, restricting hours removes opportunities, smaller orders take longer to build positions.

And a strategy whose edge is smaller than its execution cost is not a strategy with a slippage problem. It is a strategy that does not work at that frequency, and measuring the cost is how you find out which one you have.

Position sizing remains what bounds the damage from any single bad fill — capital divided by twenty as the ceiling per position, under the divide-by-20 rule.

Frequently asked questions

What is slippage? The difference between the price you expected and the price you got, arising from spread, latency, market impact, and gaps.

Is slippage always bad? It can occasionally be favourable, but it is systematically negative on average because you are paying for immediacy.

Why is my live performance worse than my backtest? Slippage is the most common reason. Backtests fill at modelled prices with no spread crossed and no liquidity consumed.

Where is slippage worst? Short-dated out-of-the-money options late in the session, overnight futures, around scheduled events, and when many participants act on the same signal at once.

How do I measure it? Log decision price and fill price on every trade, then examine the distribution by time of day and instrument rather than the average.

Disclaimer: This article is educational content about trading mechanics and software. It is not investment advice, financial advice, tax advice, legal advice, or a recommendation to buy or sell any security or futures contract, nor a recommendation of any strategy, platform, broker, or firm. Any contracts, specifications, figures, or firm rules named are described for illustration and are subject to change without notice. Futures and options trading involve substantial risk of loss and are not suitable for all investors; futures are leveraged and losses can exceed the amount deposited. Please read Characteristics and Risks of Standardized Options before trading options. Automated trading carries additional risks including software defects, connectivity failures, missed or duplicated signals, broker API changes, and outages that may prevent orders from being placed, modified, or cancelled. Past performance does not indicate future results, and no configuration, position-sizing rule, or risk setting can guarantee a profit or prevent a loss.

StaxInvesting LLC sells self-hosted trading software. It is not a broker-dealer, futures commission merchant, investment adviser, proprietary trading firm, or financial institution, and it does not manage accounts, hold member funds, place trades on behalf of members, or access member brokerage accounts. Members run the software in their own cloud environment, connect their own brokerage accounts under their own credentials, and are solely responsible for their configuration, their credential security, their compliance with any third-party terms or firm rules, and every trade executed in their account. Exchange specifications, firm rules, and platform details described here reflect publicly available information as of publication and change frequently; always verify against current official sources. Consult a qualified financial adviser, tax professional, and attorney regarding your individual circumstances.