Uniswap Labs collects fees from trades conducted through its interfaces.

Uniswap Labs, established by Hayden Adams in 2018, is a software development company that specializes in creating products for the Uniswap Protocol. This includes the development and maintenance of various applications like the Uniswap web app, a mobile wallet, and an NFT aggregator.

Uniswap Labs acts as a developer and maintainer of the Uniswap Protocol. The company functions independently from the decentralized governance of the protocol.

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Uniswap Labs

# Uniswap Labs Average trading volume (per user) Methodology

## 1. Overview

Trading volume average per user measures the average USD trading volume per daily active user on Uniswap. This metric indicates user engagement intensity by dividing total daily trading volume by the number of unique users who generated fees on that day. The calculation uses fee collection data to reverse-engineer trading volumes and identifies users through fee-generating transaction patterns across Uniswap's multi-chain deployment.

## 2. Data sources

- **Multi-chain token transfer events**: Token transfer events from Ethereum, Arbitrum, Base, BSC, Polygon, Optimism, and Avalanche capturing fees paid to Uniswap collector addresses
- **Multi-chain transaction records**: Transaction data from the same 7 blockchains providing user address identification and transaction context
- **UniswapX Fill events**: Parsed `Fill` events from UniswapX Dutch order reactor contracts on Ethereum for auction-based trading fees
- **End-of-day price feeds**: Token price data for USD conversion of fee amounts collected in various tokens
- **Token metadata**: Token decimal specifications for proper amount normalization across different token standards

## 3. Step-by-step calculation

### Component A: Fee collection identification
- **Purpose**: Identify all fee payments made to Uniswap across multiple chains and trading mechanisms
- **Logic**: Track token transfers where the sender is a known Uniswap router contract address and the recipient is a designated Uniswap collector address. Router addresses and collector addresses are maintained as hardcoded lists for each supported blockchain. For UniswapX on Ethereum, additionally identify Dutch auction fees by finding transfers to collector addresses within transactions containing `Fill` events from UniswapX reactor contracts. Apply date filters to exclude fees after December 25, 2025 when interface fees were set to zero per the UNIfication proposal. Exclude transfers involving specific denylisted tokens
- **Key fields**: `block_timestamp` for daily grouping, `transaction_hash` for transaction identification, `from_address` for user identification, `token_address` and `value` for fee amounts, `to_address` for collector validation

### Component B: Trading volume calculation
- **Purpose**: Convert collected fees back to original trading volumes using known fee rate structures
- **Logic**: Apply reverse calculation using time-dependent fee rates to derive trading volumes from collected fees. Use a fee rate of 0.15% for transactions before April 10, 2024, and 0.25% for transactions afterward. Calculate trading volume as `fees / fee_rate` for each fee collection event. Convert all fee amounts to USD using end-of-day price feeds and apply decimal corrections based on token metadata. Aggregate daily trading volumes by summing all calculated volumes for each day
- **Key fields**: `fees` converted to USD, `timestamp` truncated to day level, calculated `trading_volume` values

### Component C: Daily active user calculation  
- **Purpose**: Count unique users who generated fees on each day across all chains and products
- **Logic**: Identify users as the transaction initiator addresses (`from_address`) from the same fee-generating transactions used in volume calculation. Use HyperLogLog aggregation to accurately count distinct users while handling cross-chain and cross-product interactions without double-counting. Create multiple dimensional breakdowns (project-level, chain-level, user-type-level, product-level) and merge HyperLogLog sketches to provide accurate distinct counts. Extract the final distinct user count from the merged HyperLogLog for project-level aggregation
- **Key fields**: `user_address` from transaction initiators, HLL aggregated `user_dau` counts, `timestamp` for daily grouping

### Final aggregation
- **Combining components**: Join daily trading volume data with daily active user counts on matching timestamps, ensuring both datasets use project-level dimensional filtering for consistent scope
- **Currency conversion**: All fee amounts converted to USD using end-of-day price feeds before volume calculation
- **Time aggregation**: Both volume and user metrics aggregated at daily boundaries using timestamp truncation to day level
- **Final calculation**: Compute trading volume average per user using safe division of total daily trading volume by daily active user count, handling edge cases where user count might be zero

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Average trading volume (per user)

Trading volume divided by daily active users.

Uniswap Labs

Average trading volume (per user)

Average trading volume (per user)

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