Liquidity providers deposit funds into MUX and receive trading fees from traders (supply-side fees).

MUX is a non-custodial exchange for perpetual contracts built on Arbitrum. The previous version of MUX was MCDEX, which was founded by Jean Miao & Liu Jie in 2021 and relaunched as MUX in Aug 2022. This dashboard does not take the MUX perpetual aggregator into account yet.

MCB tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). MUX's investors include Delphi Ventures, DeFiance Capital, Robot Ventures, etc.

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# MUX Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) for Mux Protocol measures the count of unique wallet addresses that have executed trading activity within any 30-day rolling window on the platform. This metric captures user engagement across Mux's perpetual derivatives trading platform, which operates on multiple blockchain networks. The calculation uses HyperLogLog probabilistic data structures to efficiently count unique users across large datasets and provides dimensional breakdowns by project, blockchain network, user type, and product.

## 2. Data sources

The MAU calculation draws from the following raw blockchain data sources:

- **Mux V1 trading events**: Parsed `Trade` events from Mux V1 liquidity pool contracts on Arbitrum and BSC networks, containing trader addresses and transaction details
- **Mux V2 position events**: Parsed `OpenPosition` and `ClosePosition` events from Mux V2 liquidity pool contracts across Arbitrum, Avalanche, BSC, Fantom, and Optimism networks
- **Blockchain transaction data**: Block timestamps and transaction hashes from the respective blockchain networks to establish event timing
- **Protocol metadata**: Chain identifiers, market sector classifications (derivatives), business segment tags (perpetual), and user type classifications

All trading events contain the trader wallet address (`trader` parameter) which serves as the unique user identifier for MAU calculations.

## 3. Step-by-step calculation

### Component A: User event extraction
- **Purpose**: Extracts all trading activity events from Mux protocol across supported blockchains
- **Logic**: The system queries parsed blockchain events from Mux V1 and V2 contracts across six blockchain networks. For each trading event (whether `Trade`, `OpenPosition`, or `ClosePosition`), it extracts the trader wallet address, block timestamp, transaction hash, and network identifier. Each event is classified with market sector "derivatives", business segment "perpetual", and user type "Trader". The events are normalized into a consistent schema regardless of the source chain or protocol version.
- **Key fields**: `block_timestamp` for timing, `trader` address as user identifier, `chain` for network classification, `transaction_hash` for uniqueness, and metadata fields for categorization

### Component B: Daily active user aggregation  
- **Purpose**: Calculates unique daily active users and converts them to HyperLogLog sketches for efficient processing
- **Logic**: Trading events are grouped by day using timestamp truncation to day boundaries. For each day, chain, user type, and product combination, the system identifies all unique trader addresses that executed transactions. These unique user sets are then converted into HyperLogLog sketches using BigQuery's `hll_count.init` function with 15-bit precision. This probabilistic data structure allows for efficient storage and merging of large user datasets while maintaining accuracy for unique counts.
- **Key fields**: `timestamp` truncated to day, `chain` identifier, `user_type` classification, `product_id` for product breakdown, and `hll` sketch containing user addresses

### Component C: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for each calendar day to calculate monthly active users
- **Logic**: A datespine is generated covering all calendar days from the earliest data through yesterday. For each day in this datespine, the system creates a 30-day window by joining with the previous 29 days using `generate_timestamp_array`. This ensures that every day has a complete 30-day lookback period, even if some days had no trading activity. The rolling windows are then joined with the daily HyperLogLog sketches to collect all user activity within each 30-day period.
- **Key fields**: `timestamp` for the window end date, `joinday` for each day within the 30-day window, and associated `hll` sketches from the daily aggregation

### Component D: MAU calculation by dimension
- **Purpose**: Computes monthly active users across four different dimensional breakdowns
- **Logic**: For each 30-day rolling window, HyperLogLog sketches are merged using `hll_count.merge_partial` and then extracted to get unique user counts using `hll_count.extract`. This process is repeated four times to create dimensional breakdowns: project-level (all users combined), chain-level (users by blockchain network), user-type-level (users by classification), and product-level (users by product). Each breakdown aggregates the appropriate subset of HyperLogLog sketches and nullifies irrelevant dimension fields.
- **Key fields**: `user_mau` as the final unique user count, `dimensions` indicating the breakdown type, and relevant dimensional identifiers (`chain_id`, `user_type`, `product_id`)

### Final aggregation
- **Combining components**: The four dimensional breakdowns are combined using UNION ALL operations to create a comprehensive dataset containing MAU calculations for all dimension combinations
- **Time aggregation**: Each record represents MAU for a specific day (ending that 30-day rolling window) with daily granularity maintained throughout
- **Final calculation**: The exact MAU value is calculated by merging HyperLogLog sketches across the 30-day window and extracting the approximate unique count, providing an efficient and accurate estimate of monthly active users

The methodology uses HyperLogLog probabilistic counting to handle large-scale user datasets efficiently while maintaining high accuracy for unique user counts across multiple blockchain networks and time periods.

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

Unique revenue-generating users over a rolling 30-day window.

MUXMCB

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown