Liquidity providers deposit funds into ApeSwap and receive trading fees from traders (supply-side fees).

ApeSwap is a non-custodial exchange protocol built originally on BNB Chain. ApeSwap was founded by an anonymous team and launched in 2021.

BANANA tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue).

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Exchanges (DEX)

ApeSwap

# ApeSwap Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average fees earned per unique daily trader on ApeSwap, a decentralized exchange (DEX) operating across Ethereum, Polygon, Arbitrum, and BSC networks. This metric answers the business question: "How much fee revenue does each active user generate on average?" The calculation divides total daily fees earned from trading activity by the number of unique daily active traders.

## 2. Data sources

The AFPU calculation relies on these raw data sources:
- **Blockchain events**: Parsed `ApePair_Swap_event` logs from Ethereum, Polygon, Arbitrum, and BSC capturing individual trades including token amounts and user addresses
- **Factory events**: Parsed `ApeFactory_PairCreated_event` logs from the same four chains identifying valid trading pairs and their configurations
- **Transaction data**: Transaction records from Ethereum, Polygon, Arbitrum, and BSC providing user addresses for proper trade attribution
- **External data**: End-of-day token price feeds for USD conversion of trading volumes
- **Token metadata**: Token information including decimal places and symbols for accurate amount calculations

## 3. Step-by-step calculation

### Component A: Trading pair identification
- **Purpose**: Identifies all valid ApeSwap trading pairs across supported chains
- **Logic**: Collects `ApeFactory_PairCreated_event` logs from Ethereum, Polygon, Arbitrum, and BSC networks. Extracts trading pair addresses along with the two constituent token addresses (`token0` and `token1`). Applies a fixed fee tier of 0.2% (calculated as 2000/10^6) to all pairs. Enriches pair data by joining with token metadata to obtain decimal places for both tokens and creates pair names by concatenating token symbols
- **Key fields**: `account_address` (pair contract), `token0_address`, `token1_address`, `fee_tier` (0.2%), `token0_decimals`, `token1_decimals`

### Component B: Trade data collection
- **Purpose**: Captures individual swap transactions with token amount changes
- **Logic**: Processes `ApePair_Swap_event` logs from all four supported chains. For each swap, calculates the net token amount change by subtracting outgoing amounts (`amount0Out`, `amount1Out`) from incoming amounts (`amount0In`, `amount1In`) for both tokens. Links swap events to transaction records to obtain the actual user address performing the trade. Filters for transactions occurring after February 10, 2021, and classifies all users as 'Trader' type
- **Key fields**: `transaction_hash`, `user_address`, `token0_amount` (net change), `token1_amount` (net change), `block_timestamp`

### Component C: Volume calculation and USD conversion
- **Purpose**: Converts token amounts to USD trading volumes with manipulation protection
- **Logic**: Joins trade data with trading pair information to access token decimal places. Normalizes token amounts by dividing absolute values by 10 raised to the token's decimal places. Converts both token amounts to USD using end-of-day price feeds matched by date, chain, and token address. Implements manipulation protection by taking the lesser of the two USD amounts (preventing artificially inflated volumes from one token having incorrect pricing). Aggregates trading volumes daily by chain and trading pair
- **Key fields**: `trading_volume` (USD), `timestamp` (daily), `chain`, `account_address`

### Component D: Fee calculation
- **Purpose**: Calculates fees earned from trading activity
- **Logic**: Takes daily trading volumes and multiplies by the fixed fee tier of 0.2% to calculate fees earned by the protocol. Aggregates fees by timestamp, chain, market sector, business segment, and product dimensions. Applies gap-filling strategy to ensure consistent daily time series data
- **Key fields**: `fees` (USD), `timestamp`, `chain_id`, `fee_tier`

### Component E: Daily active user counting
- **Purpose**: Counts unique traders per day across all chains
- **Logic**: Extracts unique user addresses from trade transactions, truncating timestamps to daily boundaries. Uses HyperLogLog (HLL) aggregation functions to count distinct users while preventing double-counting of users who trade on multiple chains or products within the same day. Creates breakdowns by project level, chain level, user type, and product level. Applies gap-filling strategy to maintain consistent daily metrics
- **Key fields**: `user_dau` (count), `timestamp`, `dimensions`, `user_type`

### Final aggregation
- **Combining components**: The `calculate_arpu` macro joins daily fees metrics with daily active user metrics by matching timestamp and data identifier ('apeswap')
- **Currency conversion**: All amounts are already converted to USD during the volume calculation step using end-of-day price feeds
- **Time aggregation**: Both fees and user counts are aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: AFPU is calculated by dividing total daily fees by the count of unique daily active users, producing the average fees generated per trader per day

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

ApeSwapABOND

Average fees per user (AFPU)

Average fees per user (AFPU)

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