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Price Impact

Price impact is the change in token price caused by your trade, and is a closely related concept to slippage.

How Price Impact Works​

Constant Product Formula​

AMMs like gSwap use the constant product formula: x * y = k

  • x = amount of token A in the pool
  • y = amount of token B in the pool
  • k = constant that must be maintained

When you trade, you're changing the ratio of tokens in the pool, which changes the price.

Example: Price Impact Calculation​

Starting pool state:

  • 1,000 $GALA tokens
  • 500 USDC tokens
  • 1,000 * 500 = 500,000 (constant k)
  • Current price: 0.5 USDC per $GALA

If you sell 100 $GALA you will receive ~45.5 USDC:

  • Pool becomes: 1,100 $GALA, ~454.5 USDC
  • 1,100 * ~454.5 = 500,000 (still same constant k)
  • New price: ~0.413 USDC per $GALA
  • Price impact: ~17.4% (the move of the pool price, from 0.5 to ~0.413; this is what quote.priceImpact reports)
  • Your average execution price is 45.5 / 100 = ~0.455 USDC per $GALA, ~9.1% below the starting price

Factors Affecting Price Impact​

Trade Size vs Pool Size​

The ratio of your trade to the pool's liquidity determines impact. For a small trade into a 50/50 constant-product pool holding a total value TVL, the average execution price is worse than the starting price by about 2 * trade / TVL, and the pool price ends about 4 * trade / TVL lower (the figure quote.priceImpact reports):

Execution price vs start ≈ trade / (TVL / 2 + trade)
Pool price move          ≈ 1 - (TVL / 2 / (TVL / 2 + trade))^2

Examples (one full-range 50/50 pool; a concentrated pool differs, so read the real figure off a quote):

  • Trading $100 in a $1M pool: ~0.02% execution, ~0.04% pool price move
  • Trading $100 in a $10K pool: ~2% execution, ~3.9% pool price move
  • Trading $100 in a $1K pool: ~17% execution, ~31% pool price move

Pool Liquidity Distribution​

In concentrated liquidity pools (like Uniswap V3/gSwap), liquidity isn't evenly distributed:

  • Active Range: Liquidity concentrated around current price
  • Out of Range: Less liquidity available at extreme prices
  • Tick Density: How much liquidity exists at each price level

Fee Tier Selection​

Different fee tiers often have different liquidity depths:

  • 0.05% pools: Usually for very stable pairs, less liquidity
  • 0.3% pools: Most common, good liquidity for many pairs
  • 1.0% pools: Volatile pairs, may have concentrated liquidity

Minimizing Price Impact​

When Trade Splitting Helps​

Note: In a simple AMM with no other activity, splitting trades doesn't reduce total price impact - the cumulative effect is the same. However, splitting can help in these scenarios:

Allow Arbitrage Between Trades​

By waiting between smaller trades, arbitrageurs can restore the pool price closer to external market prices:

import BigNumber from 'bignumber.js';

// Split trades with delays to allow arbitrage
const tradeSize = '100';
const numTrades = 10;

for (let i = 0; i < numTrades; i++) {
  // Quote each slice fresh: the pool moves between slices, so the bound must move with it.
  const quote = await gSwap.quoting.quoteExactInput('GALA|Unit|none|none', 'GUSDC|Unit|none|none', tradeSize);
  const tx = await gSwap.swaps.swap('GALA|Unit|none|none', 'GUSDC|Unit|none|none', quote.feeTier, {
    exactIn: tradeSize,
    amountOutMinimum: new BigNumber(quote.amountOut).multipliedBy('0.99').toFixed(), // 1% tolerance
  });

  await tx.confirm();

  // Wait for potential arbitrage to restore price
  await new Promise((resolve) => setTimeout(resolve, 5000));
}

Benefit from Concentrated Liquidity Ranges​

In concentrated liquidity pools, different price ranges have different liquidity depths. Smaller trades may stay within high-liquidity ranges:

  • Large trade: May exhaust concentrated liquidity and move into sparse ranges
  • Small trades: Each trade may complete within the concentrated range

Estimating Price Impact​

Before Trading​

Always get a recent quote to understand the expected price impact:

// For exact input (selling a specific amount) - automatically finds best pool
const quote = await gSwap.quoting.quoteExactInput(
  'GALA|Unit|none|none',
  'GUSDC|Unit|none|none',
  '100',
);

console.log(`Best fee tier: ${quote.feeTier}`);
console.log(`Current price: ${quote.currentPrice.toString()}`);
console.log(`New price: ${quote.newPrice.toString()}`);
// priceImpact is negative for an adverse move (-0.01 is 1%), so print its size.
console.log(`Price impact: ${quote.priceImpact.abs().multipliedBy(100).toFixed(2)}%`);
console.log(`Expected output: ${quote.amountOut} USDC`);

Price Impact vs Slippage​

Key Differences​

AspectPrice ImpactSlippage
CauseYour trade sizeMarket movement + your trade
PredictabilityCalculable from pool stateUnpredictable
ControlReduce by smaller trades or splitting across poolsMitigate with tolerance settings

Best Practices​

Pre-Trade Analysis​

  1. Check pool liquidity across different fee tiers
  2. Calculate expected price impact using quotes
  3. Consider trade splitting for large amounts
  4. Monitor market conditions and volatility

During Execution​

  1. Use appropriate slippage protection accounting for price impact
  2. Monitor transaction status for unexpected failures
  3. Be prepared to adjust strategy if conditions change

Post-Trade Review​

  1. Compare actual vs expected execution
  2. Analyze price impact accuracy from quotes
  3. Learn from results to improve future trading
  • Slippage - How market movement affects execution price
  • Liquidity Concentration - Understanding pool depth and concentration
  • Fees - How fees interact with liquidity provision

Price impact is a fundamental cost of trading on AMMs. Understanding and minimizing it through proper trade sizing and timing is crucial for efficient trading.