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Dolomite

# Dolomite Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the daily average fees generated per active user on the Dolomite protocol. This metric is calculated by dividing total daily fees by the number of daily active users, providing insight into the average revenue contribution per user. AFPU helps assess user monetization effectiveness and protocol efficiency across Dolomite's multi-chain lending and trading platform.

## 2. Data sources

- **DolomiteMargin contract events**: Parsed events from Arbitrum, Base, Ink, Berachain, and Ethereum including `LogIndexUpdate`, `LogTrade`, `LogDeposit`, `LogWithdraw`, `LogTransfer`, `LogLiquidate`, `LogVaporize`, `LogBuy`, `LogSell`
- **Market configuration events**: `LogAddMarket` events for market definitions and token associations
- **Fee configuration events**: `LogSetEarningsRate` and `LogSetEarningsRateOverride` events for protocol fee split settings
- **Liquidation parameter events**: `LogSetLiquidationSpreadPremium` events for dynamic liquidation fee calculation
- **VesterProxy contract events**: `PositionClosed` and `VestingPositionCreated` events for oARB option revenue tracking
- **End-of-day price feeds**: USD pricing data for all supported tokens across chains
- **Token metadata**: Token symbols, decimals, and addresses for proper amount conversion
- **States data**: Backup market price data from Dolomite's internal price oracles

## 3. Step-by-step calculation

### Component A: Interest fee calculation
- **Purpose**: Calculate fees earned from lending interest on borrowed positions
- **Logic**: Start with `LogIndexUpdate` events that track borrow and supply index changes over time. For each index update, identify all outstanding loan positions (negative balances) at that time. Calculate interest accrued by multiplying the change in borrow index by the principal amount of each loan. Apply fee split percentages from `LogSetEarningsRate` events (with market-specific overrides from `LogSetEarningsRateOverride`) to determine protocol revenue share. Convert token amounts to USD using token decimals and end-of-day price feeds, with backup pricing from states data when primary prices unavailable.
- **Key fields**: `borrow_index`, `previous_borrow_index`, `par_amount`, `supply_side_fee_share`, `interest_fees_amount_usd`

### Component B: Trading fee calculation  
- **Purpose**: Calculate fees from internal AMM trades within Dolomite
- **Logic**: Process `LogTrade` events that represent trades through Dolomite's internal AMM. Apply a fixed 0.3% fee rate to all internal trading volume. Extract input and output market IDs and amounts, then join with market definitions to get token addresses and decimals. Convert input amounts to USD values using appropriate token decimals and price feeds. Calculate trading fees as 0.3% of USD trading volume.
- **Key fields**: `input_amount`, `output_amount`, `input_market_id`, `output_market_id`, `amount_usd`

### Component C: Liquidation fee calculation
- **Purpose**: Calculate fees earned from liquidation events
- **Logic**: Process `LogLiquidate` events to identify liquidation transactions. Join with `LogSetLiquidationSpreadPremium` events to determine dynamic liquidation spread premiums for both held and owed markets. Apply a base liquidation spread of 5% multiplied by the premium multipliers for both markets involved. Convert liquidated amounts to USD and multiply by the calculated spread percentage to determine liquidation fees.
- **Key fields**: `liquidation_amount`, `liquidation_spread_premium`, `owed_market_id`, `held_market_id`, `liquidation_volume_usd`

### Component D: oARB option revenue calculation
- **Purpose**: Calculate revenue from oARB (option ARB) token exercise events
- **Logic**: Track oARB option lifecycle by joining `VestingPositionCreated` events with `PositionClosed` events using `vesting_id`. Extract ETH amounts paid when positions are closed, representing option exercise revenue. Convert ETH amounts to USD using end-of-day price feeds for proper revenue accounting.
- **Key fields**: `vesting_id`, `revenue_amount`, `revenue_amount_usd`

### Component E: Daily active user calculation
- **Purpose**: Count unique users interacting with the protocol each day
- **Logic**: Identify user addresses from all DolomiteMargin contract interactions including deposits (`LogDeposit`), withdrawals (`LogWithdraw`), internal trades (`LogTrade`), external trades (`LogBuy`, `LogSell`), transfers (`LogTransfer`), and liquidations (`LogLiquidate`, `LogVaporize`). Extract user addresses from various event parameters like `takerAccountOwner`, `makerAccountOwner`, `accountOwner`, etc. Use HyperLogLog aggregation to efficiently count distinct user addresses per day across all chains and interaction types.
- **Key fields**: `user_address`, `user_dau`, `block_timestamp`

### Final aggregation
- **Combining components**: Sum all fee components (interest fees, trading fees, liquidation fees, oARB revenues) by day to get total daily fees. Aggregate daily active users using HyperLogLog merge operations to handle cross-chain and cross-activity counting
- **Currency conversion**: All fee components are converted to USD using end-of-day price feeds matched by timestamp, token address, and chain. Backup market prices from states data fill gaps when primary price feeds unavailable
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation. Missing days are filled with zero values to maintain consistent time series
- **Final calculation**: Apply the `calculate_arpu` macro which divides total daily fees by daily active user count to produce average fees per user. Results are processed through finalization steps including gap-filling and chain availability filtering

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

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Average fees per user (AFPU)

Average fees per user (AFPU)

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