Understanding Slippage: Why Your Live Trades Never Match Your Backtest
You backtest a strategy. It shows a 14% annualized return with a Sharpe ratio of 1.3. You run it live for three months. The return is 3.2%. What happened?
In most cases, slippage and fees are the answer. They are the silent drag on every live trading system, and they are almost always underestimated in backtests.
What Slippage Is
Slippage is the difference between the price at which you intended to enter or exit a trade and the price at which you actually filled.
When a backtest executes at bar N+1's open price, that is the theoretical price. In live markets, your market order interacts with the order book. If the spread is 0.04% and your order moves the price against you by another 0.03%, your actual fill is 0.07% worse than the theoretical open price.
This may seem trivial. For a strategy that makes 0.15% per trade on average, a consistent 0.07% slippage on entry and 0.10% on exit means 0.17% of cost per round trip — wiping out the entire expected profit.
The Components of Real Fill Cost
When you enter and exit a trade, you pay:
Exchange fees: Binance and Bybit charge 0.075% for taker orders (market orders that cross the spread) and 0.020% for maker orders (limit orders that add liquidity). Most retail strategies are taker-only — every entry and exit crosses the spread. That is 0.075% × 2 = 0.15% per round trip, minimum.
Bid-ask spread: On liquid pairs like BTC/USDT, the spread is often 0.01-0.02%. On smaller altcoins, it can be 0.1-0.5%. If your strategy relies on mid-price, every trade is worse than mid by half the spread on entry and half on exit.
Market impact: If your order size is large relative to the order book depth at the best price levels, your order will fill at progressively worse prices. For a $100 position on BTC/USDT, this effect is negligible. For $50,000, it becomes significant.
Execution delay: In live markets, there is latency between signal generation and order submission. In high-frequency environments, this matters enormously. For strategies on 1h and 4h charts, it is usually immaterial, but not zero.
Default Settings in Quantinger
Quantinger's default slippage is 0.05% on entry and 0.10% on exit. Combined with default fees of 0.075% taker (applied to both entry and exit), the total round-trip cost is:
0.05% + 0.075% + 0.10% + 0.075% = 0.30%
For a strategy with an average trade return of 0.5%, this means 60% of the gross profit is consumed by execution cost. The net return is 0.20%.
This is not a bug in the default settings — it is an accurate reflection of reality for small accounts trading liquid crypto pairs with market orders. If your strategy cannot clear this hurdle consistently, it does not have edge in live markets, regardless of how impressive the zero-slippage backtest looks.
Adjusting for Your Context
The correct slippage setting depends on:
Market liquidity: BTC/USDT and ETH/USDT on Binance are extremely liquid — 0.05% entry slippage is reasonable. Small caps with $2M daily volume require 0.5-1.0% slippage assumptions. If your strategy cannot survive 1% slippage on smaller pairs, it will not work live.
Trade frequency: High-frequency strategies (1m timeframe, many trades per day) accumulate fee costs faster than low-frequency ones. A strategy that makes 0.08% per trade and runs 20 trades per day generates 20 × 0.30% = 6.0% in costs per day. It needs to make more than 6% gross per day to be profitable — a nearly impossible bar.
Order type: If your strategy can use limit orders (willing to wait for fill rather than crossing the spread), maker fees apply: 0.020% instead of 0.075%. This changes the math significantly for strategies where fill certainty is not critical.
The Conservative Approach
When backtesting a new strategy, start with higher slippage than you think is necessary. If the strategy is profitable at 0.15% entry / 0.20% exit slippage, it almost certainly survives real-world execution. If it only works at 0.00% slippage, it will fail live.
A strategy that survives aggressive slippage assumptions has demonstrated cost robustness — one of the most important properties a live trading strategy can have. Slippage is one variable you cannot control in live markets. The only control you have is in how conservatively you model it before committing capital.