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 trading volume (per trade) Methodology

## 1. Overview

The trading volume average per trade count metric measures the average USD value per trade on Clipper DEX. This metric answers the business question: "What is the typical size of a trade on Clipper?" It is calculated by dividing the total daily trading volume by the total number of unique trades for the same day.

## 2. Data sources

The calculation uses several key data sources:
- **Blockchain events**: Parsed `Swapped` events from multiple Clipper contract versions across Ethereum, Polygon, Optimism, and Arbitrum blockchains, including `ApproximateCaravelExchange`, `VerifiedCaravelExchange`, `CaravelExchange`, `ExchangeInterface`, `VerifiedExchange`, `DirectExchange`, `PackedVerifiedExchange`, and `PackedExchange` contracts
- **Transaction data**: Transaction records from Ethereum, Polygon, Optimism, and Arbitrum containing user addresses and transaction metadata
- **Token metadata**: Token information including decimal precision and symbol data for proper amount conversion
- **External data**: End-of-day token price feeds providing USD prices for accurate volume calculation

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Identifies all swap transactions across Clipper's multi-chain deployment
- **Logic**: Extracts `Swapped` events from various Clipper contract versions across four blockchains. Each event contains `inAsset` and `outAsset` token addresses along with `inAmount` and `outAmount` values. The system joins these events with transaction data to obtain user addresses and transaction metadata. All trades are classified with standardized business metadata including chain, business line as 'Exchange AMM', market sector as 'exchanges', and business segment as 'dex'
- **Key fields**: `transaction_hash`, `log_index`, `inAsset` (token0_address), `outAsset` (token1_address), `inAmount` (token0_amount), `outAmount` (token1_amount), `user_address`, `block_timestamp`

### Component B: Volume calculation with decimal correction
- **Purpose**: Converts raw token amounts to properly formatted USD values
- **Logic**: Joins trade events with token metadata to obtain decimal precision for each token. Raw token amounts are divided by 10 raised to the power of the token's decimal places to get actual token quantities. The system then joins with end-of-day price feeds to convert both token amounts to USD values. To prevent price manipulation, the calculation uses the lesser of the two USD amounts from the token pair using the `LEAST` function. All processing is aggregated to daily granularity
- **Key fields**: `token0_amount` (decimal-corrected), `token1_amount` (decimal-corrected), `trading_volume` (USD), `timestamp` (daily)

### Component C: Trading volume aggregation
- **Purpose**: Sums all trading volumes by day and metadata dimensions
- **Logic**: Aggregates the USD trading volumes calculated in the previous step by summing all `trading_volume` values grouped by daily timestamp, chain, market sector, business segment, and product identifiers. This creates the total daily trading volume for Clipper across all supported chains
- **Key fields**: `trading_volume` (daily sum), `timestamp`, `chain_id`, `market_sector_id`, `business_segment_id`

### Component D: Trade count calculation
- **Purpose**: Counts the number of unique trades per day
- **Logic**: Uses the same base trade data but counts distinct `transaction_hash` values instead of summing volumes. The aggregation is performed at the same dimensional level as the volume calculation to ensure proper alignment. Each unique transaction hash represents one trade regardless of how many swap events it contains
- **Key fields**: `trade_count` (distinct transaction count), `timestamp`, `chain_id`, `market_sector_id`, `business_segment_id`

### Final aggregation
- **Combining components**: The trading volume and trade count metrics are joined on timestamp and dimensional fields to create matched daily pairs
- **Currency conversion**: All amounts are converted to USD using end-of-day price feeds with anti-manipulation logic applied during the volume calculation phase
- **Time aggregation**: All calculations use daily timestamp truncation with consistent daily boundaries across all components
- **Final calculation**: The metric divides the total daily trading volume by the total daily trade count using safe division to handle cases where trade count might be zero, resulting in the average USD value per trade for each day

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

ClipperSAIL

Average trading volume (per trade)

Average trading volume (per trade)

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