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Slippage

Slippage is the difference between the price a strategy expected when it decided to trade and the price at which the order actually filled, expressed in points, currency, or basis points.

Quick answer: Slippage is the difference between the price a strategy expected when it decided to trade and the price at which the order actually filled, expressed in points, currency, or basis points.

In simple words

Slippage is the money that quietly leaks out between the price you saw and the price you got. Part of it is the bid-ask spread you must cross, part is your own order pushing the price as it eats the book, and part is the market moving in the moments between your decision and your fill. It is usually small per trade but, multiplied across many trades, it is one of the biggest reasons a good-looking backtest disappoints live.

Purpose

Understanding slippage lets a quant separate a strategy's theoretical edge from its net-of-costs edge, budget execution cost realistically, and reject strategies whose paper profit is smaller than the slippage they would incur.

Visual explanation

Slippage

Decomposition of slippage into spread, market impact, and decision-to-fill delay.

Order Types on the Price LadderMarket — fills now at best priceLimit — only at set price or betterStop — becomes market once triggeredPrice →Sell Limit (above)Buy Stop (trigger)Market priceBuy Limit (below)

Professional explanation

Defining the benchmark price

Slippage is only meaningful relative to a reference price, and the choice of reference matters. Common benchmarks are the mid-price at decision time, the last traded price when the signal fired, or the arrival price when the order reached the market. A strategy that decides on a bar close but cannot trade until the next tick will show slippage relative to that close even before any spread. Being explicit about the benchmark is the first discipline; comparing fills against an unrealistic benchmark (like the low of the day) produces the flattering fantasy that ruins live results.

The three sources

Slippage decomposes into three additive parts. Spread cost is half the bid-ask spread you cross to trade immediately. Market impact is the extra adverse move your own order causes by consuming depth — larger and more temporary for aggressive orders, and roughly increasing with the square root of order size relative to typical volume. Delay (or timing) cost is the market's own drift between decision and fill, which can be positive or negative but is adverse on average for signal-following strategies chasing a move. Total slippage is spread plus impact plus delay.

Expressing slippage in basis points

To compare across instruments and price levels, slippage is normalised to basis points of the traded price: one basis point is 0.01 percent. A fill 2 points worse than a 25,000 benchmark is 2 / 25,000 = 0.00008 = 0.8 bps. Working in bps lets you add slippage to other costs (brokerage, STT, exchange fees) on a common scale and set a per-trade cost budget that a strategy's edge must clear. High-turnover strategies are judged on net bps per trade after all frictions.

Impact scales with size and thins with liquidity

For a given instrument, impact grows as your order becomes large relative to available depth and daily volume. A widely used rule of thumb models temporary impact as proportional to the square root of participation rate (your size divided by market volume) scaled by volatility. The practical consequence is a capacity limit: a strategy that works at one lot may be uneconomic at fifty lots in the same illiquid strike, because impact rises faster than the edge. Liquidity and slippage are two views of the same thing.

Modelling slippage in a backtest

A credible backtest injects slippage explicitly rather than assuming perfect fills. The simplest defensible model is a fixed per-trade cost (say a spread-based number of ticks); better models scale slippage with the spread and volatility of each bar, and best models add a size-dependent impact term. Whatever the model, it should be conservative: it is far safer to overestimate slippage and reject a marginal strategy than to underestimate it and deploy one whose edge evaporates on contact with the market. Slippage assumptions should be stress-tested by doubling them and checking the strategy still survives.

Slippage versus other frictions

Slippage is an implicit cost — it never appears on a contract note, unlike brokerage, STT, GST, exchange transaction charges and stamp duty, which are explicit. Total transaction cost is the sum of both. A dangerous error is to model only the explicit charges (which are easy to look up) and ignore slippage (which requires judgement), producing a backtest that undercounts the real cost of trading. For frequent intraday systems, slippage frequently dominates the explicit charges.

Formula

Slippage (bps) = ((Fill − Benchmark) / Benchmark) × 10,000 × side

Benchmark = reference price at decision or arrival; Fill = actual average execution price; side = +1 for buys, −1 for sells so that a worse fill is always a positive cost. Total slippage ≈ spread cost + market impact + delay cost. Multiply per-trade bps by round-trip trade count to size the annual drag.

Practical example

Illustrative example (Indian market)

Your system signals a Nifty long on the 25,000 bar close (benchmark 25,000). By the time the market order reaches the exchange the ask is 25,003 and you fill one lot (75) at 25,003. Slippage = (25,003 − 25,000) / 25,000 × 10,000 = 1.2 bps, or 3 points × 75 = ₹225 on entry. On the round trip (entry plus exit) you might pay ~2.4 bps, roughly ₹450 per lot before brokerage and STT. If the strategy trades 200 round trips a year at one lot, that is about ₹90,000 of slippage alone — which must be subtracted from gross profit before judging whether any edge remains.

Illiquid weekly options strikes on the NSE can show spreads of several rupees on a premium of, say, 40 — a spread of 5 on 40 is 1,250 bps, dwarfing any explicit charge. This is why slippage, not brokerage, is usually the binding constraint for options-selling and scalping systems, and why capacity is reached quickly in far OTM strikes.

Limitations

  • Slippage is an estimate, not an observed constant — real fills vary trade to trade
  • It is invisible on the contract note, so it is easy to omit and hard to attribute
  • Impact models are approximations; true impact depends on unseen order-book dynamics
  • Assumptions that are too optimistic silently convert losing strategies into apparent winners
  • Slippage is regime-dependent — it widens sharply in volatile or thin conditions your backtest may under-sample

Why it matters in practice

  • For high-turnover strategies, slippage is often the single largest cost and the main gap between backtest and live
  • Slippage sets a strategy's capacity — the size beyond which impact overwhelms the edge

Common mistakes

  • Backtesting with zero slippage or perfect close-price fills, overstating every result
  • Benchmarking fills against the day's high or low instead of the decision or arrival price
  • Modelling only explicit charges (brokerage, STT) and ignoring the larger implicit slippage
  • Assuming per-trade slippage stays constant when size grows, ignoring rising market impact
  • Using a single average slippage figure that hides the fat tail of bad fills in volatile spells
  • Ignoring that slippage compounds with turnover — a tiny per-trade cost becomes huge across thousands of trades

Professional usage

Execution desks treat slippage as a measured, attributed cost, not an afterthought. They benchmark every fill against a defined arrival or VWAP price, decompose the shortfall into spread, impact and timing, and feed that back to size orders and choose algorithms. Strategy research includes a transaction-cost model calibrated to the desk's own historical fills, and a candidate strategy must beat that cost model by a comfortable margin — not by a hair — before it is funded. The governing principle is that an edge you cannot capture after realistic slippage is not an edge.

Key takeaways

  • Slippage is the gap between expected and filled price, made of spread, market impact and delay.
  • Express it in basis points to compare across instruments and add it to other costs.
  • It scales with size and thins with liquidity, so it sets a strategy's capacity limit.
  • Model it conservatively and stress it — a strategy that only works with optimistic slippage is not deployable.

Frequently asked questions

What is slippage in trading?
Slippage is the difference between the price a strategy expected when it decided to trade and the price it actually filled at. It is an implicit cost made up of the bid-ask spread, the market impact of your own order, and the market's drift between decision and fill.
What causes slippage?
Three things: crossing the bid-ask spread to trade immediately, the market impact of your order consuming depth, and the price moving between your decision and your fill. All three push the fill away from your benchmark price, and together they make up total slippage.
How do you calculate slippage in basis points?
Take the fill price minus the benchmark price, divide by the benchmark, multiply by 10,000, and sign it so a worse fill is positive. For example, filling a buy at 25,003 against a 25,000 benchmark is (3 / 25,000) × 10,000 = 1.2 bps.
Why does my backtest beat my live trading?
Very often the answer is unmodelled slippage. If the backtest assumes perfect close-price fills, it captures profit that a real order pays away in spread and impact. Adding a realistic slippage model usually closes most of the gap.
How much slippage should I assume in a backtest?
Enough to be conservative for your instrument and size. A common approach is a spread-based per-trade cost scaled by volatility, plus an impact term for larger orders. Then stress-test by doubling the assumption and checking the strategy still survives.
What is market impact?
Market impact is the adverse price move your own order causes by consuming order-book depth. It grows roughly with the square root of your size relative to typical volume, so large orders in thin instruments move the price against themselves as they fill.
Is slippage the same as the bid-ask spread?
No. The spread is one component of slippage — the cost of crossing from bid to ask. Slippage also includes market impact from sweeping multiple levels and the delay cost of the price drifting between decision and fill.
Does slippage appear on my contract note?
No. Slippage is an implicit cost embedded in your fill price, unlike brokerage, STT, GST, exchange charges and stamp duty, which are explicit line items. Total transaction cost is the sum of the explicit charges and the invisible slippage.
Why is slippage worse in options?
Many options strikes, especially far out-of-the-money ones, are thinly traded with wide spreads relative to their premium. A spread of a few rupees on a small premium is enormous in percentage terms, so slippage often dominates all other costs in options execution.
How does slippage limit strategy capacity?
As you trade larger size, market impact rises faster than the edge, so beyond some size the slippage exceeds the profit per trade. That size is the strategy's capacity limit, and it is set primarily by the liquidity of the instruments it trades.
Can slippage ever be favourable?
The delay component can occasionally move in your favour if the market drifts your way between decision and fill, giving positive slippage. But the spread and impact components are always a cost, and on average, for signal-chasing strategies, total slippage is adverse.
How is slippage different from latency?
Latency is the time delay between decision and fill; slippage is the price cost that results, partly from that delay. Lower latency reduces the delay component of slippage but does nothing about the spread and impact components.
Does slippage matter for a low-frequency strategy?
Less than for a high-frequency one, because the cost is paid on fewer trades. A strategy trading a few times a month in liquid instruments can absorb slippage easily, whereas one trading hundreds of times a day lives or dies by it.
How do professionals reduce slippage?
They slice large orders over time, post passive limits to earn rather than pay the spread when urgency is low, use execution algorithms that adapt to liquidity, and benchmark every fill so the cost is measured and controlled rather than merely hoped to be small.

Voice search & related questions

Natural-language questions people ask about Slippage.

What is slippage in simple terms?
It is the money lost between the price you expected and the price you actually got. It comes from the spread, your order moving the market, and the price shifting while you trade.
Why is my real trading worse than my backtest?
Usually because the backtest ignored slippage. Real orders pay the spread and push the price, so the fills are worse than a perfect close-price assumption.
How do I measure slippage?
Compare your fill price to the price when you decided to trade, then express the gap in basis points. Multiply by how often you trade to see the yearly drag.
Is slippage the same as the spread?
No. The spread is just one part. Slippage also includes your order moving the market and the price drifting before you fill.
Why is slippage so bad in options?
Because many strikes are thinly traded with wide spreads compared to their small premium, so a few rupees of spread is a huge percentage cost.
Does slippage really matter that much?
For frequent traders, yes. A tiny cost per trade adds up across thousands of trades and is often the biggest reason a strategy fails live.

Sources & references

    Last reviewed 11 July 2026. Educational content only — not investment advice. Markets and rules change; verify current conventions with SEBI, NSE/BSE and your broker.

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    Educational content only — not investment advice. Examples use illustrative numbers and simplified models. Algorithmic trading and derivatives involve substantial risk. See our Risk Disclosure and SEBI Disclaimer.