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

Curve is a non-custodial exchange protocol built originally on Ethereum. Curve was founded by Michael Egorov and launched in 2020.

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

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Curve

# Curve Average trading volume (per user) Methodology

## 1. Overview

Trading volume average per user measures the average daily trading volume per daily active user on the Curve protocol. This metric provides insight into user engagement intensity by dividing the total USD value of trades by the number of unique users who traded on each day. The calculation identifies all swap transactions across Curve's various pool types, converts volumes to USD, and divides by the count of distinct users to show the average volume per active trader.

## 2. Data sources

The calculation relies on several key data sources:

- **Blockchain events**: Parsed Ethereum event logs from Curve pool contracts, including `TokenExchange`, `TokenExchangeV2`, and `TokenExchangeUnderlying` events from StablePool, TwoCryptoPool, and TriCryptoPool contract types
- **Transaction data**: Ethereum transaction records to identify the originating user addresses for each trade
- **External data**: End-of-day token price feeds for USD conversion and token metadata including decimal precision and symbols
- **Pool configuration**: Curve pool metadata specifying token arrays, addresses, and decimal configurations for each trading pair

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Identifies all swap transactions across Curve pool contracts
- **Logic**: Extracts trade events from multiple Curve contract versions including v1 StablePool events (`TokenExchange`, `TokenExchangeV2`, `TokenExchangeUnderlying`) and v2 crypto pool events (`TokenExchange` from TwoCryptoPool and TriCryptoPool). Each event captures the pool address, token IDs being swapped, and raw token amounts. Transaction data is joined to identify the user address (`from_address`) who initiated each trade.
- **Key fields**: `block_timestamp`, `transaction_hash`, `log_index`, pool `address`, `sold_id`, `bought_id`, `tokens_sold`, `tokens_bought`, and `user_address`

### Component B: Trading volume calculation  
- **Purpose**: Converts raw token amounts to USD trading volumes with manipulation filtering
- **Logic**: Joins trade events with pool configuration data to map token IDs to actual token addresses and decimal precision. Raw token amounts are normalized by dividing by 10 raised to the token's decimal places. Both tokens in each swap are converted to USD using end-of-day price feeds. To filter out potential price manipulation, the calculation takes the lesser USD value between the two tokens in each trade. Volumes are aggregated daily by summing across all trades, pools, and chains.
- **Key fields**: `token0_address`, `token1_address`, normalized `token0_amount`, `token1_amount`, and final `trading_volume` in USD

### Component C: Daily active users calculation
- **Purpose**: Counts unique users who traded on each day using scalable distinct counting
- **Logic**: Extracts unique user addresses per day from the same trade transaction data. Users are classified as 'Trader' user type since they performed swap transactions. Uses HyperLogLog (HLL) data structure for efficient distinct counting that can handle large datasets. Creates multiple dimensional aggregations including project-level (all users across Curve), chain-level, user-type-level, and product-level breakdowns.
- **Key fields**: `user_address`, `timestamp`, `user_type`, and aggregated `user_dau` count

### Final aggregation
- **Combining components**: The trading volume metric (Component B) and daily active users metric (Component C, using project-level aggregation) are joined by timestamp to align daily values
- **Currency conversion**: All token amounts are converted to USD using end-of-day price feeds, with the manipulation filtering applied by taking the minimum USD value between token pairs
- **Time aggregation**: Both components use daily time boundaries (timestamp truncated to day level) to ensure alignment
- **Final calculation**: The average trading volume per user is calculated by dividing the daily total trading volume by the daily active user count using safe division to handle cases where DAU might be zero

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

Average trading volume (per user)

Trading volume divided by daily active users.

CurveCRV

Average trading volume (per user)

Average trading volume (per user)

Competitive landscape