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BACKTESTING · SLIPPAGE

Crypto Backtest Slippage: Fixed Bps vs Liquidity-Based Assumptions

A fixed slippage of a few basis points is easy to model and often wrong. Slippage depends on order size, liquidity and volatility at the moment of trading.

By ChartsPod Editorial Team · Reviewed by ChartsPod Research
Published · Updated · 5 min read

Short answer

Fixed-bps slippage applies the same cost to every trade; liquidity-based slippage scales cost with order size relative to available depth and with volatility. Fixed bps is acceptable for small orders on liquid markets with stable conditions. For larger orders, thinner altcoins or strategies that trade during volatile moments (breakouts, liquidations), model slippage from depth or volume, or at least use higher bps for volatile bars. Test results under a stressed slippage assumption.

Two models

Slippage modelsSlippage models. Left, Fixed bps: Same cost every trade; Simple, transparent; Ignores size and volatility; OK for small, liquid. Right, Liquidity-based: Cost grows with size/depth; Higher in volatile bars; Needs depth or volume data; Better for size or alts.FIXED BPSSame cost every tradeSimple, transparentIgnores size and volatilityOK for small, liquidLIQUIDITY-BASEDCost grows with size/depthHigher in volatile barsNeeds depth or volume dataBetter for size or alts
Choose by size and market. Original ChartsPod editorial graphic.

Example

TradeOrder / depth near priceFixed 3 bpsLiquidity-based
Quiet BTC1%3 bps2 bps
Breakout BTC8%3 bps15 bps
Altcoin25%3 bps60 bps
Illustrative slippage per trade (bps)Illustrative slippage per trade (bps): Quiet BTC 2 bps; Breakout BTC 15 bps; Altcoin 60 bps.ILLUSTRATIVE SLIPPAGE PER TRADE (BPS)Quiet BTC2 bpsBreakout BTC15 bpsAltcoin60 bps
Fixed bps understates cost where it matters most. Original ChartsPod editorial graphic.

A practical approach

If depth data is unavailable, approximate: slippage bps = base + k × (order size ÷ average volume per bar), with higher base on volatile bars (e.g. when range exceeds 2× ATR). Calibrate k on a few real fills or careful observation of the book.

Slippage modellingSlippage modelling: Order size vs depth or volume; Higher cost on volatile bars; Separate assumptions per market; Stress test at 2× slippage; Compare with real fills when possible.SLIPPAGE MODELLINGOrder size vs depth or volumeHigher cost on volatile barsSeparate assumptions per marketStress test at 2× slippageCompare with real fills when possible
A model you can defend beats a convenient constant. Original ChartsPod editorial graphic.

Calibrating with real fills

If you trade the strategy live, record the intended price at signal time and the actual average fill. After 30 to 50 trades, the median difference is a realistic slippage estimate for your size and market; the worst 10% shows what volatile moments cost. Feed those numbers back into the backtest rather than keeping the original guess.

Conclusion

Use fixed bps only for small orders on liquid markets; otherwise scale slippage with size, liquidity and volatility, and stress-test it.

Related: ChartsPod Backtesting: Set Fees and Slippage Before Comparing Results, Stop-Loss Trigger vs Fill Price: Plan for Slippage in Fast Markets.

Set slippage assumptions before comparing strategies.

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Put Crypto Backtest Slippage next to price, flow and positioning in one workspace.

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Questions readers ask

What slippage should I assume?

Depends on size, market and volatility; stress-test at higher values.

Is fixed bps wrong?

It is a simplification suitable for small, liquid trades.

How do I model liquidity-based slippage?

Scale cost with order size relative to depth or volume, higher on volatile bars.

Sources and methodology

Backtesting principles follow TradingView's Pine Script documentation on strategies, repainting and non-standard charts, and ChartsPod's strategies-and-backtests guide summary, as read on 17 October 2026. All numbers are illustrative and do not describe a real strategy's performance.

  1. TradingView Pine Script: Strategies — simulated fills and assumptions.
  2. ChartsPod documentation — guides for order flow, derivatives, alerts, backtests, journal and workspaces.

This article explains research tools and workflows. It is not financial advice, does not recommend buying or selling any asset and does not predict prices. Crypto derivatives carry a risk of rapid and total loss of margin.

CHARTSPOD EDITORIAL EDITION · RESEARCH AND EDUCATION ONLY · NOT FINANCIAL ADVICE.