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

Voltz Protocol is a non-custodial Automated Market Maker (AMM) for Interest Rate Swaps deployed on Ethereum.

Voltz DAO owns and governs the protocol. They do not currently take a cut of the total trading fees paid by traders (revenue). Voltz’s investors include Framework, Fabric Ventrues etc.

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Voltz

# Voltz Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the average daily fee revenue generated per daily active user on the Voltz protocol. This metric answers the question: "How much fee revenue does each active user generate on average?" The calculation divides total daily fees by the number of distinct daily active users, providing insights into user monetization efficiency and revenue per user trends.

## 2. Data sources

The AFPU calculation relies on multiple blockchain and external data sources:

- **Ethereum event logs**: Parsed Voltz V1 contract events including `Swap`, `Mint`, `Burn`, `FullyCollateralisedSwap`, and `PositionLiquidation` events
- **Arbitrum event logs**: Parsed Voltz V1 contract events including `Swap`, `Mint`, and `Burn` events from the VAMM (Virtual Automated Market Maker) contracts
- **Pool creation events**: `IrsInstance` events from Factory contracts that provide token metadata and decimal precision information
- **End-of-day token price feeds**: USD price data for converting fee amounts from native tokens to USD values
- **Token metadata registry**: Token information including decimal places and contract addresses for proper amount calculations

## 3. Step-by-step calculation

### Component A: Trading fees extraction

- **Purpose**: Capture fees generated from interest rate swap trading activities
- **Logic**: Extract trading fees from `Swap` events on both Ethereum and Arbitrum chains, plus `FullyCollateralisedSwap` events on Ethereum. The `cumulativeFeeIncurred` field contains the fee amount in native token units. Join with corresponding `IrsInstance` pool creation events to obtain token metadata including the underlying token address and decimal precision. Convert amounts to proper decimal representation by dividing by 10 raised to the token's decimal places.
- **Key fields**: `cumulativeFeeIncurred` for fee amounts, `underlyingToken` for token addresses, `underlyingTokenDecimals` for decimal conversion

### Component B: Liquidation fees extraction

- **Purpose**: Capture fees from liquidated interest rate swap positions
- **Logic**: Extract liquidation rewards from `PositionLiquidation` events on both Ethereum and Arbitrum. The `liquidatorReward` field represents the fee paid to liquidators. Similar to trading fees, join with pool creation events to get token metadata and convert to proper decimal representation using the same decimal division approach.
- **Key fields**: `liquidatorReward` for liquidation fee amounts, `underlyingToken` and `underlyingTokenDecimals` for token identification and conversion

### Component C: Daily active user identification

- **Purpose**: Count distinct users interacting with the protocol each day
- **Logic**: Identify users from three types of activities across Ethereum and Arbitrum: traders from `Swap` and `FullyCollateralisedSwap` events (using `recipient` and `trader` fields), depositors from `Mint` events (using `owner` field), and withdrawers from `Burn` events (using `owner` field). Truncate timestamps to daily boundaries and deduplicate user addresses using HyperLogLog algorithms to handle large-scale user counting efficiently.
- **Key fields**: `recipient`, `trader`, and `owner` fields containing user addresses, `block_timestamp` for daily aggregation

### Component D: Fee aggregation and USD conversion

- **Purpose**: Combine all fee sources and standardize to USD values
- **Logic**: Union trading fees and liquidation fees into a single dataset, truncating timestamps to daily boundaries. Join with end-of-day token price feeds to convert native token amounts to USD equivalents. Sum all fee amounts by day, chain, and other dimensional attributes to create daily fee totals.
- **Key fields**: Combined `amount` fields from both fee sources, `token_address` for price feed joins, converted USD amounts

### Final aggregation

- **Combining components**: Join daily aggregated fees with daily active user counts on matching timestamp and dimensional attributes (chain, product, etc.)
- **Currency conversion**: All fees converted to USD using end-of-day price feeds before aggregation to ensure consistent currency representation
- **Time aggregation**: Both fees and user counts aggregated to daily granularity using timestamp truncation to day boundaries
- **Final calculation**: Divide total daily fees (in USD) by the count of distinct daily active users to produce average fees per user. Apply forward-fill strategy for missing days to ensure continuous time series data

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

Voltz

Average fees per user (AFPU)

Average fees per user (AFPU)

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