DEX aggregators

Oku Trade

# Oku Trade Average trading volume (per trade) Methodology

## 1. Overview

The trading volume average per trade count metric measures the average USD value of each trade on the OkuTrade decentralized exchange. This metric is calculated by dividing the total daily trading volume by the total number of trades for the same day, providing insight into the typical trade size on the platform. The calculation focuses exclusively on OkuTrade v3 protocol activity on the XDC blockchain.

## 2. Data sources

The calculation relies on several key data sources:
- **Blockchain events**: Parsed XDC blockchain `Swap` events from OkuTrade v3 liquidity pools, containing token amounts, transaction details, and user addresses
- **Pool creation events**: XDC blockchain `PoolCreated` events from OkuTrade v3 Factory contracts, establishing trading pair relationships and fee tier information
- **Token metadata**: Token symbol, decimal precision, and identifier information for proper amount normalization and pair naming
- **External data**: End-of-day token price feeds in USD for accurate volume conversion
- **Transaction data**: XDC transaction hashes and timestamps for trade identification and daily aggregation

## 3. Step-by-step calculation

### Component A: Trading volume calculation
- **Purpose**: Calculate the total USD trading volume for OkuTrade across all trading pairs on a daily basis
- **Logic**: Start by extracting all `Swap` events from OkuTrade v3 pools on the XDC blockchain, capturing the `amount0` and `amount1` fields representing token quantities exchanged. Join these events with trading pair metadata from `PoolCreated` events to identify token addresses and decimal precision. Convert token amounts to actual values by dividing by the appropriate decimal factors (typically 10^18 for most tokens). Join with end-of-day price feeds to convert both token amounts to USD values. To prevent price manipulation, use the minimum USD value between the two tokens in each swap as the trade volume. Aggregate all trades by day using timestamp truncation
- **Key fields**: `amount0` and `amount1` for token quantities, `token0_address` and `token1_address` for token identification, `token0_decimals` and `token1_decimals` for normalization, `price_usd` from price feeds

### Component B: Trade count calculation  
- **Purpose**: Count the total number of individual trades on OkuTrade on a daily basis
- **Logic**: Extract the same `Swap` events from OkuTrade v3 pools, but focus on counting unique transactions rather than calculating volumes. Group events by daily timestamp boundaries and count distinct `transaction_hash` values, treating each unique transaction as one trade regardless of how many swap events occurred within that transaction. This approach ensures that complex transactions with multiple swaps are counted as single trades
- **Key fields**: `transaction_hash` for trade identification, `block_timestamp` for daily grouping, `log_index` for event ordering

### Final aggregation
- **Combining components**: Join the daily trading volume totals with daily trade counts using the timestamp as the matching key. Both components are aggregated to the same daily grain to ensure proper alignment
- **Currency conversion**: USD conversion occurs at the individual trade level using end-of-day price feeds, with the minimum USD value logic applied before daily aggregation
- **Time aggregation**: All data is truncated to daily boundaries using timestamp truncation, with both volume and count metrics calculated for the same day periods
- **Final calculation**: Divide 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.*

Oku Trade

Average trading volume (per trade)

Average trading volume (per trade)

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