Understanding Slippage

Slippage and MEV

Setting a low slippage tolerance is the simplest defense against toxic-MEV. Since searchers exploit slippage for price manipulation, transactions with lower slippage tolerance could provide less opportunity for toxic-MEV exploitation from trades.

Additionally, slippage modeling generally incorporates statistics into a smart order routing algorithm to deliver the optimal trade route.

Nevertheless, these solutions are incomplete. Even with optimal slippage, MEV bots may still derive value from your trades.

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On Solana

In Solana's Token Swap Program, a generic swap involves the input amount_in, which represents the amount of token the user wants to trade, and minimum_amount_out, which denotes the minimum amount of output tokens necessary to avoid excessive slippage:

/// Swap instruction data
pub struct Swap {
    /// SOURCE amount to transfer, output to DESTINATION is based on the exchange rate
    pub amount_in: u64,
    /// Minimum amount of DESTINATION token to output, prevents excessive slippage
    pub minimum_amount_out: u64,
}

The minimum amount of output tokens is connected to the actual number of output tokens by the slippage, ensuring that:

$$\min(N_{out}^A) = N_{out}^A - S^A \times N_{out}^A$$

The slippage can be derived as follows:

$$S^A = \frac{N_{out}^A - \min(N_{out}^A)}{N_{out}^A} \%$$