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# Etherex Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the daily average fee revenue generated per active user on the Etherex decentralized exchange. This metric provides insight into user value and monetization efficiency by dividing total daily fees by the number of daily active users. The calculation encompasses both liquidity provider fees and protocol revenue across Etherex V2 and V3 deployments on the Linea blockchain.

## 2. Data sources

- **Blockchain events**: Parsed Linea blockchain events including `Swap` events from Etherex V2 Pair contracts and V3 Pool contracts, `Flash` events from V3 Pool contracts, and `VotesIncentivized` events from V2 FeeDistributor contracts
- **Transaction data**: Linea transaction records containing user addresses and transaction metadata
- **External data**: End-of-day token price feeds for USD conversion, token metadata including decimals and symbols for amount normalization
- **Configuration data**: Pool fee tier settings, protocol fee splits, and trading pair creation events that define fee structures over time

## 3. Step-by-step calculation

### Component A: Daily active user identification
- **Purpose**: Identify unique users who interact with Etherex protocols daily
- **Logic**: Extract user addresses from two types of activities: trading (swap events) and flash loans. For trading, identify `Swap` events from both V2 Pair contracts using `Pair_Swap_event` and V3 Pool contracts using `Pool_Swap_event` on Linea. For flash loans, identify `Flash` events from V3 Pool contracts. Link these events to Linea transaction records to extract the actual user address from the `from_address` field, distinguishing end users from contract intermediaries
- **Key fields**: User addresses (`from_address`), event timestamps (`block_timestamp`), contract addresses for protocol identification

### Component B: Trading volume calculation  
- **Purpose**: Calculate USD trading volumes across all Etherex pools
- **Logic**: Process swap events differently for V2 and V3. For V2, calculate token amount changes using the difference between `amount0In` minus `amount0Out` and `amount1In` minus `amount1Out` from `Pair_Swap_event`. For V3, use direct `amount0` and `amount1` values from `Pool_Swap_event`. Join with trading pair metadata to get token addresses and decimal places. Correct token amounts by dividing by 10 raised to the token's decimal places. Convert to USD by multiplying corrected amounts by end-of-day token prices, using the lesser of the two token USD values to filter out price manipulation
- **Key fields**: Token amounts (`amount0`, `amount1`), token addresses, decimal places, USD prices (`price_usd`)

### Component C: Fee calculation
- **Purpose**: Calculate total fees from trading activity and additional revenue streams
- **Logic**: Apply dynamic fee rates to USD trading volumes. For each pool, determine the active fee tier using pool creation and fee adjustment events, applying the correct rate based on event timestamps. Calculate supply-side fees as trading volume multiplied by fee tier multiplied by (1 minus protocol fee split). Calculate protocol revenue as trading volume multiplied by fee tier multiplied by protocol fee split. Add voting bribe revenue from `VotesIncentivized` events, converting token amounts to USD using end-of-day prices and correcting for token decimals
- **Key fields**: Fee tiers (`fee_tier`), protocol fee splits (`fee_split`), bribe amounts and token addresses

### Component D: User aggregation with HyperLogLog
- **Purpose**: Accurately count distinct daily active users across all activities
- **Logic**: Combine trading users and flash loan users into a single dataset. Use HyperLogLog algorithm to count distinct users per day, handling potential overlaps between trading and flash loan activities. Aggregate at multiple dimension levels including overall project, by chain, by user type, and by product version
- **Key fields**: User addresses aggregated using HyperLogLog functions

### Final aggregation
- **Combining components**: Sum all fee streams (supply-side fees and protocol revenue) to get total daily fees. Count distinct daily active users using HyperLogLog aggregation
- **Currency conversion**: All amounts converted to USD using end-of-day price feeds, with token amounts corrected for decimal places before conversion
- **Time aggregation**: Data aggregated to daily boundaries using `timestamp_trunc` to day level
- **Final calculation**: Divide total daily fees (in USD) by daily active user count to produce average fees per user. Missing days are filled with zeros to maintain complete time series continuity

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

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