Liquidity providers deposit funds into zkSwap and receive trading fees from traders (supply-side fees). Traders receive token rewards for their trades through the Swap2Earn incentive program (token incentives).

zkSwap Finance is a non-custodial Swap-to-Earn DeFi exchange protocol built on zkSync Era (originally a fork of Uniswap). zkSwap Finance was founded by pseudonymous ThunderNoah, etc., and launched in 2023. 

ZF token holders own and govern the protocol via Snapshot vote. They currently take a cut of the total trading fees paid by traders (revenue).

governance

github

twitter

discord

etherscan

website

Exchanges (DEX)

zkSwap Finance

# zkSwap Finance Average trading volume (per user) Methodology

## 1. Overview

This metric calculates the average daily trading volume per unique active user on the zkSwap decentralized exchange. It measures trading efficiency by dividing the total USD trading volume by the number of daily active users (DAU), providing insight into how much volume each user generates on average. The metric helps assess user engagement and trading intensity on the zkSwap protocol.

## 2. Data sources

- **zkSync Era swap events**: Parsed `Swap` events from zkSwap v1 pair contracts containing token exchange amounts and user addresses
- **zkSync Era factory events**: Parsed `PairCreated` events from zkSwap v1 factory contract identifying valid trading pairs and their token addresses
- **zkSync Era transaction data**: Transaction records providing user addresses (`from_address`) for each swap transaction
- **End-of-day token price feeds**: Daily USD price data for tokens traded on zkSwap
- **Token metadata**: Token information including decimal places and symbols for proper amount normalization and pair identification

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extract raw swap data from zkSwap v1 DEX on zkSync Era
- **Logic**: Parse `Swap` events from zkSwap v1 pair contracts, capturing `amount0In`, `amount0Out`, `amount1In`, `amount1Out` fields along with `sender` and transaction details. Join with zkSync Era transaction records to get the actual user address (`from_address`) who initiated each swap transaction.
- **Key fields**: `amount0In/Out` and `amount1In/Out` (token amounts), `sender` (contract user), `from_address` (actual user), `transaction_hash`, `block_timestamp`

### Component B: Trading pair identification
- **Purpose**: Identify valid zkSwap trading pairs and their token compositions
- **Logic**: Use `PairCreated` events from zkSwap v1 factory contract to map pair contract addresses to their underlying `token0` and `token1` addresses. Join with token metadata to get decimal places and symbols for proper amount calculation and pair naming.
- **Key fields**: `pair` address, `token0` and `token1` addresses, token `decimals`, token `symbols`

### Component C: Trade volume calculation
- **Purpose**: Calculate USD trading volume for each swap transaction
- **Logic**: For each swap, calculate net token amounts by subtracting outgoing from incoming amounts (`amount0In - amount0Out` and `amount1In - amount1Out`). Take absolute values and normalize using token decimal places. Convert both token amounts to USD using end-of-day price feeds. Apply price manipulation filtering by taking the minimum USD value between the two tokens in each swap. Aggregate trades to daily level by summing USD volumes.
- **Key fields**: `token0_amount`, `token1_amount` (normalized), `trading_volume` (USD value)

### Component D: Daily active user counting
- **Purpose**: Count unique users who traded each day
- **Logic**: Extract user addresses from the same trade transactions used for volume calculation. Group by day and identify users as 'Trader' type. Use HyperLogLog sketches to count distinct users across multiple dimensions including project-level aggregation. Focus on the 'project_dbt_tag' dimension for total project DAU.
- **Key fields**: `user_address`, `user_type` ('Trader'), `user_dau` (distinct count)

### Final aggregation
- **Combining components**: Join daily trading volume totals with daily active user counts on the same date, using the project-level DAU aggregation ('project_dbt_tag' dimension)
- **Currency conversion**: All trading volumes are converted to USD using end-of-day price feeds, with price manipulation filtering applied by taking the minimum value between both tokens in each swap
- **Time aggregation**: Both components use daily time boundaries (timestamp truncated to day level)
- **Final calculation**: Divide the total daily trading volume by the daily active user count using safe division to handle cases where DAU might be zero, resulting in the average trading volume per user in USD

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

Average trading volume (per user)

Trading volume divided by daily active users.

zkSwap FinanceZF

Average trading volume (per user)

Average trading volume (per user)

Competitive landscape