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# Etherex 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 Etherex protocol. This metric quantifies user engagement depth by showing how much volume each active user generates on average. The calculation divides total daily trading volume by the count of daily active users, where users are identified from both trading activities and flash loan usage.

## 2. Data sources

- **Blockchain swap events**: Parsed `Swap` events from Etherex v2 pairs (`Pair_Swap_event`) and Etherex v3 pools (`Pool_Swap_event`) on Linea blockchain
- **Flash loan events**: Parsed `Flash` events from Etherex v3 pools (`Pool_Flash_event`) on Linea blockchain  
- **Transaction data**: Linea transaction records containing user addresses and transaction metadata
- **Trading pair creation events**: `PairCreated` events from Etherex v2 factory and `PoolCreated` events from Etherex v3 factory contracts
- **External data**: End-of-day price feeds for token-to-USD conversion, token metadata including symbols and decimal places
- **Pool configuration events**: Fee tier settings and fee split configurations from pool factory contracts

## 3. Step-by-step calculation

### Component A: Trading volume extraction and processing

- **Purpose**: Extract and process raw trading activity from Etherex swap events
- **Logic**: The system captures swap events from both Etherex v2 pairs and v3 pools on Linea. For v2 swaps, token amount changes are calculated as `amountIn` minus `amountOut` for each token. For v3 swaps, the direct `amount0` and `amount1` values represent the token changes. Each swap event includes the pool address, transaction hash, log index, and sender address. The raw token amounts are joined with trading pair metadata to identify the specific tokens involved and their decimal configurations.
- **Key fields**: `token0_amount` and `token1_amount` representing the absolute token quantities traded, `account_address` identifying the trading pool, `user_address` from transaction records identifying the trader

### Component B: USD conversion with manipulation protection

- **Purpose**: Convert token amounts to USD values while preventing price manipulation
- **Logic**: Raw token amounts are first corrected for decimal places by dividing by 10 raised to the power of each token's decimal configuration. The corrected amounts are then joined with end-of-day price feeds for both tokens in each trading pair. To prevent price manipulation attacks, the system calculates the USD value for both tokens separately and takes the minimum value between `token0_amount * token0_price` and `token1_amount * token1_price`. This approach ensures that artificially inflated prices for one token cannot distort the volume calculation.
- **Key fields**: `token0_amount` and `token1_amount` after decimal correction, `price_usd` from end-of-day price feeds, resulting `trading_volume` in USD

### Component C: Daily active user counting

- **Purpose**: Count unique daily users across all Etherex activities
- **Logic**: The system identifies daily active users from two activity types: trading (swap events) and flash loan usage. User addresses are extracted from transaction records linked to both swap events and flash loan events. Users participating in either activity type on a given day are counted as active. The system uses HyperLogLog sketches for efficient distinct user counting, allowing for accurate deduplication when the same user performs multiple activities. Users are aggregated at the project level to get total daily active users across all Etherex activities.
- **Key fields**: `user_address` from transaction records, `user_dau` representing distinct daily active users using HyperLogLog aggregation

### Final aggregation

- **Combining components**: Daily trading volume totals are joined with daily active user counts on the timestamp field. Both metrics use daily grain aggregation, ensuring alignment between volume and user activity measurements.
- **Currency conversion**: All volume calculations are performed in USD using end-of-day price feeds, with the minimum price method preventing manipulation
- **Time aggregation**: Both trading volume and user counts are aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: The metric applies safe division of total daily trading volume by daily active user count, handling cases where DAU might be zero. The result represents the average USD trading volume generated per active user on each day. A standardization macro applies consistent formatting and fills any missing days with zeros.

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

Average trading volume (per user)

Trading volume divided by daily active users.

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Average trading volume (per user)

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