Liquidity providers deposit funds into Vertex and earn the spread between maker and taker orders.

Vertex is a non-custodial exchange built on Arbitrum that offers spot, perpetuals, and money markets with universal cross-margin accounts. Vertex launched in 2023, and was founded by Darius Tabatabai and Alwin Peng.

The Vertex team own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). Vertex's investors include Wintermute, Hack VC, Jane Street, etc.

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Vertex

# Vertex Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the daily revenue generated per active user on the Vertex Protocol. This metric is calculated by dividing daily revenue by daily active users (DAU). Vertex Protocol is a decentralized derivatives exchange that operates across multiple blockchains, and ARPU helps assess the average value generated per user from trading activities. The calculation uses 100% of trading fees as revenue since market makers are primarily incentivized through bid-ask spreads rather than fee rebates.

## 2. Data sources

The ARPU calculation relies on the following raw data sources:

- **Parsed `FillOrder` events**: Events from `OffchainExchange_FillOrder` and `OffchainBook_FillOrder` contracts across multiple chains including Arbitrum, Base, Blast (Blitz), Sonic, and Avalanche
- **Event parameters**: Key fields include `feeAmount` (trading fees in 18-decimal USD format), `subaccount` (unique user identifier), `isTaker` (boolean flag to identify taker orders), and standard blockchain metadata like timestamps and transaction hashes
- **Chain availability data**: Used to filter results to periods when each blockchain was actively supported by the protocol

## 3. Step-by-step calculation

### Component A: Fee collection
- **Purpose**: Extract all trading fees generated from spot and perpetual trading activities
- **Logic**: Parse `FillOrder` events from both `OffchainExchange` and `OffchainBook` contracts across all supported chains. Filter events where `isTaker` is true to prevent double-counting, since both maker and taker orders emit `FillOrder` events. Convert the `feeAmount` field from 18-decimal format to standard USD amounts by dividing by 10^18. Classify all activity as "Perpetual trading" under the "derivatives" market sector
- **Key fields**: `feeAmount` (converted to standard USD format), `isTaker` (filtering flag), `address` (account generating fees), chain identifier, and timestamp for daily aggregation

### Component B: User identification
- **Purpose**: Identify unique daily active users engaged in trading activities
- **Logic**: Extract user identifiers from the same `FillOrder` events used for fee collection. Use the `subaccount` field as the unique user identifier, which represents trading accounts on the Vertex platform. Classify all users as "Trader" user type within the "derivatives" market sector and "perpetual" business segment
- **Key fields**: `subaccount` (unique user identifier), chain identifier, user classification as "Trader", and timestamp for daily aggregation

### Component C: Revenue aggregation
- **Purpose**: Calculate total daily revenue from trading activities
- **Logic**: Aggregate the converted fee amounts by day, chain, and product. Revenue equals 100% of collected fees since the protocol operates on a fee-based model where market makers are primarily incentivized through bid-ask spreads rather than fee rebates. Apply daily timestamp truncation and sum all fee amounts within each day
- **Key fields**: Aggregated `amount` values representing daily revenue in USD, grouped by timestamp, chain, and product dimensions

### Component D: Daily active user aggregation  
- **Purpose**: Count distinct daily active users efficiently across multiple dimensions
- **Logic**: Use HyperLogLog sketches to efficiently count distinct users while supporting multiple aggregation dimensions. Create breakdowns by overall project level, individual chains, user types, and product IDs. The HyperLogLog approach enables accurate distinct counting while managing memory efficiently for large datasets
- **Key fields**: HyperLogLog sketches of `user_dau` values, aggregated across timestamp, chain, user type, and product dimensions

### Final aggregation
- **Combining components**: The `calculate_arpu` macro combines the revenue and DAU metrics by matching on timestamp, chain, and product dimensions. Revenue values are divided by corresponding DAU counts for the same time period and dimension breakdown
- **Currency conversion**: No additional currency conversion is required since fees are already denominated in USD within the source events
- **Time aggregation**: Both components use daily timestamp truncation to align on consistent daily boundaries. The calculation maintains daily granularity throughout
- **Final calculation**: ARPU equals daily revenue divided by daily active users, with a fill_zeros strategy applied to populate missing dates with zero values rather than null values. Chain availability filtering ensures results only include periods when each blockchain was actively supported

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

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Average revenue per user (ARPU)

Average revenue per user (ARPU)

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