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

Mummy Finance is a non-custodial exchange for spot and perpetual contracts built on Fantom, Optimism, and Arbitrum. Mummy Finance was founded by an anonymous team and was launched in December 2022.

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

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Mummy Finance

# Mummy Finance Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average amount of trading fees generated per unique daily active user on the Mummy protocol. This metric answers the business question: "How much revenue does each active user generate on average per day?" The calculation divides total daily fees collected across all trading activities by the number of distinct daily active users across Mummy's perpetual trading platform on Arbitrum, Fantom, and Optimism.

## 2. Data sources

The AFPU calculation uses the following raw data sources:

- **Blockchain events**: Parsed smart contract events from Mummy's Vault contracts on Arbitrum, Fantom, and Optimism networks, including `IncreasePosition`, `DecreasePosition`, and `Swap` events for user activity tracking
- **Fee collection events**: Parsed `CollectMarginFees` events from perpetual trading and `CollectSwapFees` events from spot trading across all supported chains
- **Token metadata**: Token symbol and decimal place information for proper fee token identification and normalization
- **External data**: End-of-day token price feeds for USD conversion of fees collected in various tokens

## 3. Step-by-step calculation

### Component A: Daily active user tracking
- **Purpose**: Identifies and counts unique daily active users across all Mummy trading activities
- **Logic**: Extracts user addresses from three types of trading events on Vault contracts: position increases, position decreases, and token swaps. On Fantom, includes events from both Vault and Vault2 contracts. All users are classified as "Trader" type within the derivatives market sector and perpetual business segment. Uses HyperLogLog probabilistic data structure for efficient distinct counting across large user sets. Aggregates users daily and provides breakdowns by chain, user type, and product level.
- **Key fields**: `account` field from trading events becomes `user_address`, `block_timestamp` for daily bucketing, `chain` for multi-chain aggregation

### Component B: Perpetual fee collection
- **Purpose**: Captures trading fees from leveraged perpetual trading activities
- **Logic**: Processes `CollectMarginFees` events from Vault contracts across Arbitrum, Fantom, and Optimism. These events represent margin fees paid by users during leveraged perpetual trading. Extracts the fee token address and fee amount for each collection event. Classifies fees under "Perpetual trading" business line within derivatives market sector.
- **Key fields**: `token` field for fee token identification, `feeTokens` field for fee amount, contract `address` for account identification

### Component C: Spot fee collection  
- **Purpose**: Captures trading fees from spot trading activities
- **Logic**: Processes `CollectSwapFees` events from Vault contracts across all three supported chains. These events represent spot trading fees paid by users during token swaps. Extracts fee token address and amount for each swap fee collection. Classifies fees under "Spot trading" business line within derivatives market sector.
- **Key fields**: `token` field for fee token identification, `feeTokens` field for fee amount, contract `address` for account identification

### Component D: Fee standardization and conversion
- **Purpose**: Standardizes fee data across different tokens and converts to USD
- **Logic**: Combines perpetual and spot fees into unified dataset. Joins with token metadata to obtain consistent token symbols and decimal specifications. Applies decimal correction based on each token's specification to normalize fee amounts. Converts all fee amounts to USD using end-of-day price feeds, ensuring consistent currency representation across different fee tokens collected.
- **Key fields**: `token_address` for metadata joining, `amount` for fee values, `symbol` for token identification

### Final aggregation
- **Combining components**: Daily active users are counted using HyperLogLog merge operations across all chains and user types. Daily fees are summed in USD across both perpetual and spot trading activities for each day
- **Currency conversion**: Fee amounts are converted to USD using end-of-day token price feeds and corrected for proper decimal places based on individual token specifications  
- **Time aggregation**: Both user counts and fee amounts use daily time boundaries (timestamp truncated to day) to ensure consistent aggregation periods
- **Final calculation**: AFPU equals total daily fees in USD divided by total daily active users. Days with no activity are filled with zero values to maintain continuous time series data

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

Mummy Finance

Average fees per user (AFPU)

Average fees per user (AFPU)

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