DEX aggregators

Oku Trade

# Oku Trade Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fees generated per active user on OkuTrade, a Uniswap V3 fork operating on the XDC blockchain. This metric answers the business question "How much fee revenue does each active user generate on average?" The calculation divides total daily fees by the number of daily active users, where fees come from both trading activity and flash loan activity, and users include anyone performing swaps or flash loans.

## 2. Data sources

The calculation relies on several key data sources:
- **Blockchain events**: Parsed `Pool_Swap_event` logs from OkuTrade V3 pool contracts on XDC blockchain capturing all token swaps
- **Flash loan events**: Parsed `Pool_Flash_event` logs from OkuTrade V3 pool contracts on XDC blockchain capturing all flash loan activities  
- **Pool creation events**: Parsed `Factory_PoolCreated_event` logs from OkuTrade V3 factory contracts providing trading pair metadata and fee tier information
- **Transaction data**: XDC blockchain transaction records providing user address information for flash loan attribution
- **External data**: End-of-day token price feeds for USD conversion and token metadata including symbols and decimal places
- **Pool metadata**: Trading pair information including token addresses, fee tiers, and pool addresses derived from factory events

## 3. Step-by-step calculation

### Component A: Trading volume calculation
- **Purpose**: Calculate USD volume from token swaps to determine trading fees
- **Logic**: Extract `Pool_Swap_event` logs containing `amount0` and `amount1` fields representing token amounts exchanged. Join with trading pair dimensions to get token addresses and decimal places. Normalize token amounts by dividing by 10 raised to the token's decimal places. Convert both token amounts to USD using end-of-day price feeds matched by date, token address, and chain. Apply anti-manipulation logic by taking the minimum USD value between the two tokens rather than summing them. Aggregate volumes daily by pool and apply the pool's fee tier percentage to calculate trading fees.
- **Key fields**: `amount0` and `amount1` (raw token amounts), `fee_tier` (pool fee percentage), `token0_address` and `token1_address` (token identifiers), normalized amounts after decimal correction

### Component B: Flash loan volume calculation  
- **Purpose**: Calculate USD volume from flash loans to determine flash loan fees
- **Logic**: Extract `Pool_Flash_event` logs containing `amount0` and `amount1` fields for borrowed token amounts. Join with XDC transaction data to identify the user address from the transaction's `from_address` field. Join with trading pair dimensions for token metadata and fee tiers. Normalize token amounts using decimal correction. Convert both token amounts to USD using end-of-day price feeds. Unlike trading volumes, sum both token amounts in USD rather than taking the minimum, since flash loans represent actual borrowed amounts rather than trades that could be manipulated. Apply the pool's fee tier percentage to calculate flash loan fees.
- **Key fields**: `amount0` and `amount1` (flash loan amounts), `from_address` (user identifier from transaction), `fee_tier` (pool fee percentage), USD amounts after price conversion

### Component C: Daily active user counting
- **Purpose**: Count unique users performing either trading or flash loan activities
- **Logic**: Identify users from two sources: trading activity using the `sender` field from `Pool_Swap_event` logs, and flash loan activity using the `from_address` field from associated transaction records. Truncate timestamps to day boundaries and deduplicate users across both activity types using union distinct operations. Count unique users per day using approximate distinct counting to handle large datasets efficiently.
- **Key fields**: `sender` (trader address from swap events), `from_address` (user address from flash loan transactions), daily timestamp boundaries for aggregation

### Component D: Pool metadata and fee tiers
- **Purpose**: Provide fee tier information and token metadata for volume and fee calculations
- **Logic**: Parse `Factory_PoolCreated_event` logs to extract pool addresses, token pair information, and fee tiers. Fee tiers are stored as basis points and converted to decimal percentages by dividing by one million. Enrich with token metadata including symbols and decimal places to enable proper volume calculations and pool identification.
- **Key fields**: `pool` (pool contract address), `token0` and `token1` (token addresses), `fee` (fee tier in basis points), `decimals` (token decimal places)

### Final aggregation
- **Combining components**: Sum daily trading fees and flash loan fees to get total daily fees per pool, then aggregate across all pools. Sum daily active users across both trading and flash loan activities while deduplicating to avoid double-counting users who perform both activities on the same day.
- **Currency conversion**: All USD conversions use end-of-day price feeds matched exactly by date, token address, and chain to ensure consistent pricing
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation to day level, ensuring consistent time alignment across fees and user counts
- **Final calculation**: Divide the total daily fees in USD by the total count of daily active users to produce the average fees per user metric. Handle edge cases by filling periods with zero fees or zero users appropriately rather than producing null values.

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

Oku Trade

Average fees per user (AFPU)

Average fees per user (AFPU)

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