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Slippage

The gap between the price a strategy assumed when it made a decision and the price actually received when the order filled.

Your ranking rule picks TATAMOTORS on Monday using Monday’s closing price of ₹742. The order reaches the exchange at Tuesday’s open and fills at ₹748. That ₹6, or 0.81%, is slippage. Nothing malfunctioned. The market moved between the moment you decided and the moment you traded.

Slippage is one of the most common reasons a live strategy underperforms the backtest that convinced you to run it.

Where it comes from

SourceWhat happens
Timing gapYou decide on one bar and fill on the next. Overnight news and the pre-open auction move the price in between.
Bid-ask spreadYou buy at the ask and sell at the bid. Half the spread is given up on each side of a round trip.
Market impactYour own order consumes the order book and pushes the price against you. NSE publishes this component as impact cost.
Partial fillsA large order clears across several price levels, so the average fill is worse than the top of the book.

How it is modelled here

Orders in a saral.money backtest fill at the next bar’s open. That is the only timing a live system can physically achieve, because you cannot fill at a close you are still observing. Slippage and transaction costs are modelled on top of that, and the cost model can apply a specific broker’s real equity-delivery charge stack rather than a generic percentage.

Sizing the drag

Slippage scales with how often you trade, not with how much you hold:

annual slippage drag = sides traded per year x slippage per side

A 20-stock portfolio that fully replaces its holdings every month trades 24 sides a year counting both buys and sells. At 10 basis points per side that is 2.4% a year before brokerage and taxes. Move to quarterly rebalancing and the same assumption costs 0.8%.

Caveats

Slippage is not a constant, and treating it as one is the mistake. Spreads widen in small caps, in the opening minutes, and in exactly the stressed markets where your strategy is trying to exit. A single flat assumption understates cost precisely when it matters.

Run the backtest twice, once at your expected slippage and once at three times that. If the edge only survives the optimistic run, you have found a cost story rather than an alpha story.

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