Liquidity providers deposit funds into Wombat Exchange and receive WOM token rewards.

Wombat Exchange is a non-custodial exchange protocol built on BNB Chain. Wombat Exchange was founded by Alex Lee and launched in April 2022.

WOM tokenholders own and govern the protocol. They currently receive all trading fees paid by traders (revenue). Wombat Exchange’s investors include Binance Labs, Animoca Brands and Hailstone Ventures.

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Wombat Exchange

# Wombat Exchange Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average amount of fees paid per daily active user on Wombat Exchange. This metric answers the business question: "How much revenue does each active user generate on average?" The calculation divides total daily fees collected by the protocol by the number of unique users who traded that day, providing insights into user value and protocol monetization efficiency.

## 2. Data sources

The calculation relies on several key data sources:

- **Wombat Exchange Swap events**: Parsed `Swap` and `SwapV2` events from various Wombat pool contracts across BSC, Arbitrum, Ethereum, Avalanche, Optimism, and Base chains, containing trade details like token addresses, amounts, and user information
- **Fee rate configuration events**: `SetHaircutRate` events from Wombat pool contracts that update fee tiers, combined with hardcoded initial fee rates for different pool types
- **Blockchain transaction data**: Transaction records from supported chains to extract user addresses and link them to swap events
- **Token metadata**: Token contract information including symbols and decimal places for proper amount normalization
- **End-of-day price feeds**: Daily token price data in USD for converting token amounts to standardized values

## 3. Step-by-step calculation

### Component A: Trade data collection
- **Purpose**: Collect all trading activity across Wombat Exchange pools on multiple chains
- **Logic**: Extract `Swap` and `SwapV2` events from various Wombat pool contracts including main pools, cross-chain pools, side pools, and specialized asset pools. Join with transaction data to get user addresses. Handle special cases by mapping certain unsupported wrapped tokens to the WOM token address to maintain consistency. Each trade record includes the trading pool address, user address, input/output token addresses, and token amounts.
- **Key fields**: `fromToken` and `toToken` addresses, `fromAmount` and `toAmount` quantities, `user_address` from transaction data, pool `account_address`, and `block_timestamp`

### Component B: Fee tier determination
- **Purpose**: Establish the fee rate applicable to each pool and time period
- **Logic**: Use hardcoded initial fee tiers for different pool types ranging from 0.00002 (0.002%) to 0.0025 (0.25%) based on pool risk and asset type. Track updates to these rates through `SetHaircutRate` events where the fee tier is extracted from the event's value parameter divided by 10^18. Apply forward-filling logic to ensure each pool has a valid fee tier for every day, carrying forward the most recent rate when no updates occur.
- **Key fields**: `fee_tier` as a decimal rate, pool `account_address`, and effective `timestamp`

### Component C: Trading volume calculation
- **Purpose**: Convert raw token amounts to standardized USD trading volumes
- **Logic**: For each trade, correct decimal places by dividing token amounts by 10 raised to the power of each token's decimal count. Convert both input and output token amounts to USD using end-of-day price feeds joined on timestamp, chain, and token address. To prevent price manipulation, take the minimum USD value between the two token sides of each trade. Aggregate all trades by day, user, and pool to get daily trading volumes.
- **Key fields**: Corrected `token0_amount` and `token1_amount`, USD-converted values, and final `trading_volume` in USD

### Component D: Fee calculation
- **Purpose**: Calculate total fees collected from trading activity
- **Logic**: For each trade's USD volume, multiply by the applicable fee tier from the fee tier component. The fee tier represents the percentage of trading volume collected as fees by the protocol. Sum all individual trade fees by day to get total daily fees across all pools and chains.
- **Key fields**: `fees` calculated as `trading_volume` multiplied by `fee_tier`

### Component E: Daily active user counting
- **Purpose**: Count unique users who traded each day
- **Logic**: Extract distinct user addresses from all trading transactions per day using HyperLogLog aggregation for efficient processing of large datasets. Users are identified by their wallet addresses that initiated swap transactions. Count users across all chains and pool types, with the user type classified as 'Trades' to distinguish from other potential user categories. Aggregate at multiple dimensional levels including project-wide, per-chain, and per-product.
- **Key fields**: Distinct `user_address` counts aggregated as `user_dau`

### Final aggregation
- **Combining components**: Join daily fees and daily active users on the same timestamp to ensure temporal alignment of the metrics
- **Currency conversion**: All monetary values are already converted to USD during the trading volume calculation step using end-of-day price feeds
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation to day level, ensuring consistent time windows
- **Final calculation**: Divide total daily fees by the count of daily active users to get the average fees per user. Apply zero-filling for days with no trading activity to maintain time series continuity and ensure the metric shows zero rather than null values during inactive periods

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

Wombat ExchangeWOM

Average fees per user (AFPU)

Average fees per user (AFPU)

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