Liquidity providers deposit funds into Clipper and receive returns generated by Clipper’s costless diversified rebalancing liquidity pools (supply-side fees). LP yields are generated from the rebalancing process itself rather than from fees charged to traders.

Clipper is a non-custodial exchange protocol built on Ethereum. Clipper was built by Shipyard Software and launched in 2021.

AdmiralDAO and SAIL token holders own and govern the protocol. They currently receive all trading fees paid by traders (revenue). Clipper's investors include Polychain, Robot Ventures, 0x Labs, etc.

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Clipper

# Clipper Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the average amount of fees collected per daily active user on the Clipper decentralized exchange. This metric answers the question "How much revenue does Clipper generate per user on average?" and is calculated by dividing total daily fees by the number of daily active users. The calculation aggregates data across multiple blockchains (Ethereum, Polygon, Optimism, and Arbitrum) and combines multiple fee collection methodologies to provide a comprehensive view of per-user revenue generation.

## 2. Data sources

- **Blockchain events**: Parsed `Swapped` events from Clipper exchange contracts across Ethereum, Polygon, Optimism, and Arbitrum, including various contract versions (ApproximateCaravelExchange, VerifiedCaravelExchange, CaravelExchange, ExchangeInterface, VerifiedExchange, DirectExchange, PackedVerifiedExchange, PackedExchange)
- **Transaction data**: Ethereum, Polygon, Optimism, and Arbitrum transaction records to identify user addresses initiating swaps
- **Subgraph data**: TheGraph subgraph events for Clipper v1 on Ethereum and Polygon containing swap details with token amounts
- **External data**: End-of-day token price feeds for USD conversion, token metadata including decimal information, and Clipper scraper v2 data providing swap information with pre-calculated USD values
- **Data types**: Daily swap event logs, transaction traces, end-of-day price feeds, token metadata, and aggregated swap data with USD valuations

## 3. Step-by-step calculation

### Component A: Daily active users calculation
- **Purpose**: Identifies and counts unique users who performed swaps each day across all supported chains
- **Logic**: Extracts `Swapped` events from Clipper contracts across Ethereum, Polygon, Optimism, and Arbitrum. Joins these events with corresponding transaction data to identify the `user_address` (from_address field in transactions). Filters events by timestamp and groups by day to count distinct users. Uses HyperLogLog data structure for efficient counting across multiple dimensions (chain, user type, product).
- **Key fields**: `block_timestamp` for daily aggregation, `transaction_hash` for joining with transaction data, `user_address` for user identification, `chain` for multi-chain aggregation

### Component B: Fee collections from subgraph data
- **Purpose**: Calculates fees using a fixed percentage methodology from TheGraph subgraph events
- **Logic**: Processes `Swapped` events from Clipper subgraphs on Ethereum and Polygon. Applies a fixed fee tier of 0.2% to the `outAmount` field to calculate fees. Handles native token wrapping by converting null addresses to wrapped native token addresses (WETH on Ethereum, WMATIC on Polygon). Aggregates fee amounts by day and converts to USD using end-of-day price feeds.
- **Key fields**: `outAmount` for fee calculation base, `outAsset` for token identification, `blockTimestamp` for daily grouping, calculated `token_amount` as 0.2% of outAmount

### Component C: Fee collections from scraped data
- **Purpose**: Calculates fees using USD value differences from comprehensive swap data
- **Logic**: Processes swap data from Clipper scraper v2 covering Ethereum, Polygon, Optimism, and Arbitrum. Calculates fees as the positive difference between `amountInUsd` and `amountOutUsd` values. Filters out swaps involving CLP tokens to focus on trading fees rather than liquidity provision. Sets fees to zero when the difference is negative or zero.
- **Key fields**: `amountInUsd` and `amountOutUsd` for fee calculation, `inTokenSymbol` and `outTokenSymbol` for filtering, `timestamp` for daily aggregation

### Component D: Fee aggregation and USD conversion
- **Purpose**: Combines multiple fee sources and standardizes values in USD
- **Logic**: Unions fee data from subgraph sources (after decimal correction and USD conversion) with scraped fee data (already in USD). Applies token decimal correction using metadata, converts token amounts to USD using end-of-day price feeds, and sums all fees by day, chain, and other relevant dimensions.
- **Key fields**: Combined `fees` amounts, `timestamp` for daily boundaries, `chain` for multi-chain aggregation, `token_address` and `token_symbol` for price lookups

### Final aggregation
- **Combining components**: Joins daily active user counts with daily fee totals using date and chain dimensions. Both metrics are aggregated at the project level across all supported chains.
- **Currency conversion**: Subgraph-based fees are converted to USD using end-of-day price feeds and corrected for token decimals, while scraped fees are already provided in USD values
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation, with consistent timezone handling across all data sources
- **Final calculation**: AFPU is calculated by dividing the sum of all daily fees (from both subgraph and scraped sources) by the count of daily active users. Days with no users or fees are filled with zero values to maintain time series continuity. The division is performed using the calculate_arpu macro with revenue_metric_id='fees' and user_metric_id='user_dau'.

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

ClipperSAIL

Average fees per user (AFPU)

Average fees per user (AFPU)

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