DEX aggregators

Oku Trade

# Oku Trade Trade count Methodology

## 1. Overview

The OKUTrade trade count metric measures the daily number of unique trades executed on OKUTrade's decentralized exchange on the XDC network. This metric provides insight into trading activity and user engagement by counting distinct transactions that contain swap events, regardless of how many individual swap events occur within each transaction. The calculation focuses on OKUTrade's v3 AMM pools and aggregates data at a daily level to track trading volume patterns over time.

## 2. Data sources

The calculation relies on the following raw data sources:
- **XDC blockchain event logs**: Parsed `Pool_Swap_event` logs from OKUTrade v3 smart contracts deployed on the XDC network
- **Transaction data**: XDC transaction metadata including timestamps, transaction hashes, and log indices for event ordering and deduplication
- **Contract metadata**: OKUTrade v3 pool contract addresses and event schemas for proper event identification

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extract and parse raw swap events from OKUTrade v3 contracts on XDC
- **Logic**: The system identifies `Pool_Swap_event` logs from OKUTrade v3 contracts on the XDC blockchain. Each event represents a token swap execution within an AMM pool. The extraction captures essential transaction metadata including `block_timestamp`, `transaction_hash`, `log_index`, contract `address`, and swap details like `sender` address and token amounts (`amount0` and `amount1`). Events are filtered to only include data from the XDC network and classified with business metadata indicating this is a DEX in the exchanges market sector
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for trade identification, `log_index` for event ordering, `address` for contract identification, `sender` for user tracking, and `amount0`/`amount1` for swap quantities

### Component B: Daily trade aggregation
- **Purpose**: Group trades by day and count unique transactions
- **Logic**: Raw trade events are processed to create daily aggregates. Timestamps are truncated to daily boundaries using day-level granularity. The system counts distinct `transaction_hash` values rather than individual events to ensure that transactions containing multiple swap events are counted as single trades. This prevents double-counting scenarios where a single user transaction might generate multiple swap events across different pools or token pairs. Data is grouped by timestamp, chain identifier, market sector, business segment, and product version
- **Key fields**: `timestamp` truncated to day, `transaction_hash` for distinct counting, `chain_id` for network identification, classification fields for business categorization

### Final aggregation
- **Combining components**: Trade events are aggregated using COUNT(DISTINCT `transaction_hash`) to produce daily trade counts, ensuring each unique transaction is counted exactly once regardless of how many swap events it contains
- **Time aggregation**: Daily boundaries are established by truncating timestamps to day level, with each day representing the count of unique trades executed within that 24-hour period
- **Data standardization**: The final metric applies standardized formatting through the finalize metric process, which includes gap-filling with zero values for days with no trading activity and applies consistent business classification and chain availability filtering
- **Final calculation**: The result is a daily time series showing the count of distinct transactions that contained at least one OKUTrade v3 swap event, representing the number of unique trades executed each day on the platform

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

Number of trades executed on a decentralized exchange.

Oku Trade

Trade count

Trade count

Competitive landscape

Chain breakdown