Trades are conducted between a signer and a sender & AirSwap takes a fee (revenue) which is assessed on the signer amount.

AirSwap is a non-custodial exchange built on multiple chains that allows direct peer-to-peer trading. AirSwap was co-founded by Don Mosites & Michael Oved and launched in 2017.

AST tokenholders own and govern the protocol. Revenue is currently distributed to a contributor tips pool and a voter rewards pool according to a set split. AirSwap DAO has not raised funds and the company that originally launched AirSwap is no longer operating.

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AirSwap

# AirSwap Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average fee revenue generated per daily active user on the AirSwap DEX aggregator platform. This metric answers the question: "How much fee revenue does each user generate on average per day?" The calculation divides total daily fee revenue by the number of daily active users, providing insight into user monetization efficiency across the platform.

## 2. Data sources

The calculation relies on several raw data sources:

- **Multi-chain swap event logs**: Parsed swap events from multiple AirSwap contract versions across Ethereum, Arbitrum, Avalanche, BSC, and Polygon networks, including `SwapERC20`, `Swap`, `Light_Swap`, and `AirSwapExchange_Filled` events
- **Transaction data**: Transaction records from all supported chains containing sender addresses and transaction metadata
- **Token metadata**: Token contract information including decimal precision and symbol data for proper amount conversion
- **End-of-day price feeds**: Daily token price data in USD for volume and fee calculations

## 3. Step-by-step calculation

### Component A: Trade data extraction
- **Purpose**: Extract and standardize swap events from multiple AirSwap contract versions across five blockchain networks
- **Logic**: The system processes swap events from various AirSwap contract versions (v0 through v4) deployed across Ethereum, Arbitrum, Avalanche, BSC, and Polygon. Each contract version has different event signatures and fee structures. For v4 contracts, fees are extracted from the `protocolFee` parameter. V3 contracts also use `protocolFee`. V2 contracts use `signerFee` for newer versions and a hardcoded 30 basis points for v0. V1 contracts have zero fees, while v0 uses the legacy `AirSwapExchange_Filled` event with zero fees. The system joins swap events with transaction data to capture user addresses from the transaction sender field. Block number filters are applied to exclude pre-deployment data (notably block 4916553 for v0 Ethereum contracts).
- **Key fields**: `signerToken`, `senderToken`, `signerAmount`, `senderAmount` (token addresses and amounts), `protocolFee`, `signerFee` (fee amounts), user addresses from transaction `from_address`, chain identifiers, and version labels

### Component B: Trading volume calculation
- **Purpose**: Convert raw token amounts to USD trading volumes with price manipulation protection
- **Logic**: Raw token amounts from swap events are first corrected for decimal precision using token metadata. Each token amount is divided by 10 raised to the power of the token's decimal places. The corrected amounts are then converted to USD using end-of-day price feeds matched by timestamp, token address, and chain. To prevent price manipulation attacks, the system calculates USD values for both tokens in each swap and takes the lesser of the two values as the final trading volume. This ensures that artificially inflated prices for one token cannot inflate the reported volume.
- **Key fields**: Decimal-corrected `token0_amount` and `token1_amount`, USD `price_usd` from price feeds, final `trading_volume` as the minimum USD value between the two tokens

### Component C: Fee calculation
- **Purpose**: Calculate total fee revenue by applying fee rates to trading volumes
- **Logic**: Fees are calculated by multiplying the USD trading volume by the applicable fee tier for each swap. Fee tiers are either extracted directly from event parameters (such as `protocolFee` or `signerFee`) or applied as hardcoded values based on the contract version. For events with fee parameters, the raw fee amount is divided by 10,000 to convert from basis points to decimal percentage. The system then multiplies this fee rate by the trading volume to get the fee amount in USD. All fees are aggregated daily by summing across all swaps.
- **Key fields**: `fee_tier` (converted to decimal), `trading_volume`, calculated `fees` as the product of volume and fee rate

### Component D: Daily active user counting
- **Purpose**: Count unique users who performed swaps each day across all chains and versions
- **Logic**: The system identifies daily active users by extracting the sender address from each transaction containing a swap event. User addresses are truncated to daily timestamps and deduplicated to count each user only once per day, regardless of how many swaps they performed. The system uses HyperLogLog (HLL) probabilistic counting to efficiently aggregate unique users across multiple dimensions including total project level, individual chains, user types, and product segments. This approach handles large-scale data efficiently while maintaining accuracy for distinct counting.
- **Key fields**: `user_address` from transaction data, daily `timestamp`, aggregated `user_dau` counts using HLL functions

### Final aggregation
- **Combining components**: Daily fee totals and daily active user counts are combined using the `calculate_arpu` macro, which performs the division of fees by users to calculate average fees per user
- **Currency conversion**: All amounts are converted to USD using end-of-day price feeds matched by date, token address, and blockchain network
- **Time aggregation**: Data is truncated to daily boundaries using timestamp truncation, with all metrics calculated and reported on a daily basis
- **Final calculation**: AFPU is calculated as total daily fees divided by total daily active users, with the result finalized using the `finalize_metric_afpu` macro which applies fill-zeros strategy for missing days and includes chain availability filtering

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

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