Manual traders feel slippage as frustration. Algo traders feel it as data — cold, measurable, and ruthlessly honest. The gap between a strategy that looks brilliant on paper and one that survives contact with real markets almost always comes down to transaction costs: commissions, bid-ask spreads, and the market impact of your own orders hitting the book.

A backtest that ignores these costs is essentially a fantasy novel with charts. Systematic traders build cost models before they build entry signals, because a high-frequency mean-reversion strategy trading 40 times per day with a 0.5-pip spread assumption can look like a retirement plan in simulation and a bill in live execution. The math compounds fast, and not in your favour.

CONCEPTModelling realistic transaction costs before backtesting is the single biggest separator between professional and amateur algo development.
WARNINGA strategy showing 20% annual returns in backtest can turn negative once accurate spreads, commissions, and slippage are applied.
KEY IDEANet expectancy — return per trade after all costs — is the only number that matters when evaluating an algo's true edge.

Spreads are not static. They widen during low liquidity, news events, and market open. An algo calibrated on midday spread data will encounter a very different world at 9:32am or during a Fed announcement. Traders who account for variable spread distributions in their cost models tend to be less surprised — and less broke — when live results arrive.

Strategy Return: Gross vs Net of Costs24%15%6%Gross-Commissions-Spreads

The practical fix is to stress-test every strategy against a range of cost scenarios — conservative, realistic, and pessimistic. Walk-forward analysis helps confirm that edge persists out-of-sample, not just in the golden era your optimiser happened to find. For foundational reading, the mechanics of bid-ask spread and the structure of slippage in execution are well covered on Investopedia, while algorithmic trading on Wikipedia provides useful context on how professional systems approach market microstructure.

Every pip and every dollar of commission is a vote against your edge. Build cost models that are brutally honest, and let the backtest hurt you before the market does.

This content is for educational purposes only and does not constitute financial product advice. Past performance is not indicative of future results. Profit Logic Ltd (ACN 688 669 936) accepts no responsibility for errors or omissions in this content or anywhere on this website. Always seek advice from a licensed financial adviser before making investment decisions.