Liquidity providers deposit funds into Wombat Exchange and receive WOM token rewards.

Wombat Exchange is a non-custodial exchange protocol built on BNB Chain. Wombat Exchange was founded by Alex Lee and launched in April 2022.

WOM tokenholders own and govern the protocol. They currently receive all trading fees paid by traders (revenue). Wombat Exchange’s investors include Binance Labs, Animoca Brands and Hailstone Ventures.

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Wombat Exchange

# Wombat Exchange Trade count Methodology

## 1. Overview

The Wombat trade count metric measures the daily number of unique trades executed on Wombat Exchange across multiple blockchains. This metric counts distinct transactions that contain swap events, providing insight into trading activity and user engagement on the platform. The calculation aggregates unique transaction hashes from parsed swap events across all Wombat pools and chains, grouped by day and various business dimensions.

## 2. Data sources

The metric relies on several key data sources:
- **Swap events**: Parsed `Swap` and `SwapV2` events from Wombat Exchange pool contracts across BSC, Arbitrum, Ethereum, Avalanche, Optimism, and Base blockchains, covering 44+ different pool types including main pools, side pools, dynamic pools, and specialized asset pools
- **Fee tier events**: Parsed `SetHaircutRate` events from Wombat pool contracts that provide dynamic fee tier updates
- **Transaction data**: Blockchain transaction records from all supported chains to obtain user addresses and transaction metadata
- **Token metadata**: Token registry data including symbols and decimal places for proper amount normalization
- **Price feeds**: End-of-day token price feeds for USD conversion and price manipulation detection

## 3. Step-by-step calculation

### Component A: Raw trade extraction
- **Purpose**: Extract all swap events from Wombat Exchange pools across multiple blockchains
- **Logic**: The system unions swap events from 44+ different pool types across 6 blockchains (BSC, Arbitrum, Ethereum, Avalanche, Optimism, Base). Each pool type has its own event schema but all contain core swap information including `fromToken`, `toToken`, `fromAmount`, and `toAmount` fields. The extraction handles special cases for unsupported wrapped tokens by mapping specific addresses to the WOM token address. Transaction data is joined to enrich swap events with user addresses from the `from_address` field in transaction records.
- **Key fields**: `block_timestamp`, `transaction_hash`, `log_index`, pool `address`, `fromToken`, `toToken`, `fromAmount`, `toAmount`, and `from_address` from transactions

### Component B: Fee tier mapping
- **Purpose**: Establish fee tier rates for each Wombat pool contract over time
- **Logic**: The system starts with hardcoded initial fee tiers for each pool type, ranging from 0.00002 (0.002%) to 0.0025 (0.25%) depending on the pool category. Cross-chain pools typically have the lowest fees, while specialized pools like WOM-related pools have higher fees. Dynamic fee updates are captured from `SetHaircutRate` events, where the `value` parameter represents the new fee tier as a proportion (converted from wei by dividing by 10^18). A forward-fill strategy ensures continuous fee tier availability by carrying forward the most recent fee tier for each pool address.
- **Key fields**: Pool `address`, `timestamp`, `fee_tier` rate, and `value` from SetHaircutRate events

### Component C: Trade data preparation  
- **Purpose**: Process and enrich raw swap data with metadata and USD conversions
- **Logic**: Trade events are aggregated to daily granularity by truncating `block_timestamp` to day level. Token amounts are corrected for decimals by dividing raw amounts by 10 raised to the power of each token's decimal places from token metadata. Fee tiers are joined based on pool address, chain, and trade timestamp. Token symbols are concatenated to create readable trading pair names. USD conversion uses end-of-day price feeds matched by token address, chain, and timestamp. A price manipulation filter applies the lesser USD value between the two tokens in each swap to avoid inflated volumes from manipulated prices.
- **Key fields**: `timestamp`, `transaction_hash`, `log_index`, `chain`, corrected `token0_amount` and `token1_amount`, `fee_tier`, and calculated USD `trading_volume`

### Final aggregation
- **Combining components**: The enriched trade data serves as input for the final trade count calculation, with all necessary metadata and validations already applied
- **Currency conversion**: USD conversion occurs during data preparation for validation purposes, but the final trade count metric is purely numerical (count of transactions)
- **Time aggregation**: Daily boundaries are established by truncating timestamps to day level, ensuring consistent daily groupings across all time zones
- **Final calculation**: The metric uses `approx_count_distinct(transaction_hash)` to count unique transactions per day, grouped by `timestamp`, `chain_id`, `market_sector_id`, `business_segment_id`, and `product_id`. The finalization macro applies a zero-fill strategy to ensure continuous daily data points and applies chain availability filtering to exclude periods when chains were not yet supported.

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

Number of trades executed on a decentralized exchange.

Wombat ExchangeWOM

Trade count

Trade count

Competitive landscape

Chain breakdown