DEX aggregators

Oku Trade

# Oku Trade Average trading volume (per user) Methodology

## 1. Overview

Trading volume average per user measures the mean daily trading volume generated per daily active user on the Okutrade decentralized exchange. This metric answers the question: "How much volume does each active user generate on average per day?" The calculation divides total daily trading volume by the number of daily active users, providing insight into user engagement depth and trading intensity on the platform.

## 2. Data sources

- **Blockchain events**: Parsed XDC blockchain event logs from Okutrade V3 smart contracts, specifically `Pool_Swap_event` logs capturing all trading activity and `Pool_Flash_event` logs capturing flash loan activity
- **Contract creation events**: XDC blockchain `Factory_PoolCreated_event` logs that define trading pairs and their metadata
- **Transaction data**: XDC blockchain transaction records used to map contract interactions to actual user addresses
- **External data**: End-of-day token price feeds for USD conversion and token metadata including decimal specifications and symbols

## 3. Step-by-step calculation

### Component A: Trading volume calculation
- **Purpose**: Calculates the total daily trading volume in USD across all Okutrade V3 trading pairs
- **Logic**: Extracts raw swap events from XDC blockchain `Pool_Swap_event` logs, capturing `amount0` and `amount1` values representing token quantities exchanged in each trade. Joins with trading pair metadata from `Factory_PoolCreated_event` logs to obtain token addresses, decimal specifications, and fee tiers. Corrects raw token amounts by dividing by 10 raised to the power of each token's decimal places. Converts corrected amounts to USD values using end-of-day price feeds matched by token address, chain, and timestamp. Applies price manipulation filtering by taking the minimum USD value between the two tokens in each pair to prevent inflated volume from manipulated prices. Aggregates all trade values by day to produce total daily trading volume
- **Key fields**: `amount0` and `amount1` (raw token quantities), `token0_address` and `token1_address` (token identifiers), `fee_tier` (trading fee rate), corrected token amounts after decimal adjustment, USD-converted values using daily price feeds

### Component B: Daily active user calculation  
- **Purpose**: Counts unique users who performed trading or flash loan activities each day
- **Logic**: Combines user addresses from two activity sources. From trading activity, extracts `contract_user_address` values from XDC blockchain `Pool_Swap_event` logs representing users who executed swaps. From flash loan activity, extracts user addresses by joining `Pool_Flash_event` logs with XDC transaction records, using the transaction `from_address` as the actual user address since flash loan events only contain contract addresses. Unions both user address sets and applies daily timestamp truncation. Counts distinct user addresses per day using approximate counting to handle large datasets efficiently
- **Key fields**: `contract_user_address` from swap events, `from_address` from transaction records for flash loans, `user_dau` (distinct user identifier), daily timestamp boundaries

### Final aggregation
- **Combining components**: Joins daily trading volume totals with daily active user counts on matching timestamp values, using an inner join to ensure both metrics exist for the calculation period
- **Currency conversion**: USD conversion occurs during trading volume calculation using end-of-day price feeds matched by token address, chain, and daily timestamp
- **Time aggregation**: All calculations use daily boundaries created by truncating blockchain timestamps to day level, ensuring consistent 24-hour periods across all metrics
- **Final calculation**: Divides total daily trading volume by daily active user count using safe division to handle cases where DAU equals zero, producing the average trading volume per user. The `finalize_metric_trading_volume_avg_per_user` macro standardizes the output schema and fills any missing days with zero values to maintain time series continuity

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

Average trading volume (per user)

Trading volume divided by daily active users.

Oku Trade

Average trading volume (per user)

Average trading volume (per user)

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