website

twitter

github

Stablecoin issuers

Fathom

# Fathom Average trading volume (per user) Methodology

## 1. Overview

The trading volume average per user metric measures the average USD trading volume per daily active user on the Fathom protocol. This metric combines trading activity from Fathom DEX with user activity from both DEX and lending products to calculate how much volume each active user generates on average. The calculation divides total daily trading volume by the number of unique daily active users across all Fathom products.

## 2. Data sources

The calculation relies on several data sources from the XDC Network:
- **DEX trading events**: Parsed `Swap` events from Fathom DEX Pair contracts containing token amount changes for each trade
- **Transaction data**: XDC Network transaction records to identify user addresses initiating trades
- **Lending activity events**: Five types of parsed events from Fathom Lending contracts including `Supply`, `Withdraw`, `Borrow`, `FlashLoan`, and `Repay` events
- **Trading pair metadata**: `PairCreated` events from Fathom DEX Factory contracts defining token pairs and fee tiers
- **Token metadata**: Token contract information including decimal places and symbols
- **End-of-day price feeds**: Daily USD price data for tokens traded on Fathom DEX

## 3. Step-by-step calculation

### Component A: DEX trading volume calculation
- **Purpose**: Calculate daily USD trading volume from all DEX swap activities
- **Logic**: Start with `Swap` events from Fathom DEX Pair contracts on XDC Network. Extract net token amount changes by calculating `amount0In` minus `amount0Out` for token0 and `amount1In` minus `amount1Out` for token1. Join with trading pair metadata to identify token addresses and decimal places. Correct token amounts by dividing by 10 raised to the power of token decimals. Convert to USD using end-of-day price feeds with a fallback mechanism that prioritizes token0 prices but uses token1 prices when token0 prices are unavailable. Sum all USD trade values by day to get total daily trading volume.
- **Key fields**: `amount0In`, `amount0Out`, `amount1In`, `amount1Out` from swap events; `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals` from trading pair metadata; `price_usd` from price feeds

### Component B: Daily active user calculation  
- **Purpose**: Count unique daily active users across all Fathom protocol activities
- **Logic**: Collect user addresses from two sources. For DEX activities, extract user addresses from transaction records linked to `Swap` events. For lending activities, extract user addresses from five event types: `user` field from `Supply` and `Withdraw` events, `user` field from `Borrow` events, `initiator` field from `FlashLoan` events, and `repayer` field from `Repay` events. Combine all user addresses and deduplicate using approximate count distinct to get the total number of unique active users per day. Create multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level aggregations.
- **Key fields**: `user_address` from transaction records, `user` from lending events, `initiator` from flash loan events, `repayer` from repay events

### Final aggregation
- **Combining components**: Join daily trading volume and daily active user data on the same timestamp. Use the project-level DAU aggregate that represents total unique users across all Fathom products.
- **Currency conversion**: Trading volume is already converted to USD during the volume calculation step using end-of-day price feeds
- **Time aggregation**: Both components use daily time boundaries with timestamp truncated to day level
- **Final calculation**: Calculate trading volume average per user by dividing total daily trading volume by daily active users using safe division to handle cases where DAU is zero. Apply finalization logic to standardize the schema and fill missing days with zero values.

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

Average trading volume (per user)

Trading volume divided by daily active users.

Fathom

Average trading volume (per user)

Average trading volume (per user)

Competitive landscape