Overcollateralized borrowers deposit funds into Liquity and receive LUSD stablecoin.

Liquity is a non-custodial stablecoin protocol built on Ethereum. Liquity was founded by Robert Lauko & Rick Pardoe and launched in 2020.

LQTY tokenholders own & govern the protocol. They currently take all of the total borrow & redemption fees paid by borrowers (revenue). Liquity’s investors include Lemniscap, Polychain, Alameda Research, etc.

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Liquity

# Liquity Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique user addresses that interacted with the Liquity protocol within a rolling 30-day period. This metric answers how many distinct users are actively engaging with Liquity's stablecoin borrowing functionality each month. The calculation uses HyperLogLog probabilistic counting to efficiently compute unique users across overlapping time windows, providing dimensional breakdowns by project level, chain, user type, and product.

## 2. Data sources

The MAU calculation relies on the following raw data sources:
- **Blockchain events**: Parsed Ethereum `LUSDBorrowingFeePaid` events from Liquity v1's BorrowerOperations contract
- **Transaction data**: Ethereum transaction records containing block timestamps and transaction hashes
- **Event logs**: Raw Ethereum event logs with log indices and contract addresses
- **Chain metadata**: Chain availability information to filter active networks

## 3. Step-by-step calculation

### Component A: User identification
- **Purpose**: Identifies active Liquity protocol users from blockchain events
- **Logic**: Extracts user addresses from `LUSDBorrowingFeePaid` events emitted by Liquity's BorrowerOperations contract on Ethereum. These events occur when users pay fees for borrowing LUSD stablecoin, indicating active protocol usage. Each event provides the borrower address, transaction details, and timestamp. Users are classified as 'Borrower' type and associated with the 'lusd' product within the 'stablecoin_issuer' business segment.
- **Key fields**: `user_address` (borrower address from event), `block_timestamp` (transaction timing), `chain` (network identifier), `user_type` (always 'Borrower'), `product_id` (always 'lusd')

### Component B: Daily active user aggregation
- **Purpose**: Calculates distinct active users per day as the foundation for MAU computation
- **Logic**: Groups user activity by day using timestamp truncation to day granularity. Creates distinct counts of user addresses per day, maintaining dimensional attributes like chain, user type, and product. Applies chain availability filtering to ensure only active networks are included. Each daily record represents the unique set of users who interacted with Liquity on that specific day.
- **Key fields**: `timestamp` (day-truncated timestamp), `user_dau` (unique user address), `timestamp_grain` (always 'day'), `chain`, `user_type`, `product_id`

### Component C: HyperLogLog initialization
- **Purpose**: Prepares daily user sets for efficient MAU calculation using probabilistic counting
- **Logic**: Initializes HyperLogLog counters for each daily user set with 15-bit precision. HyperLogLog enables efficient approximation of distinct counts when merging overlapping time windows. Groups daily user data by timestamp, chain, user type, and product, creating HLL representations of the daily unique user sets.
- **Key fields**: `hll` (HyperLogLog counter initialized from daily users), `timestamp`, `chain_id`, `user_type`, `product_id`

### Component D: Rolling window creation
- **Purpose**: Establishes 30-day rolling windows for MAU calculation
- **Logic**: Generates a complete datespine covering all days from the earliest user activity to the present, ensuring no gaps in the time series. For each day in the datespine, creates a 30-day lookback window by generating timestamps for the current day plus the previous 29 days. Joins this rolling window structure with the daily HLL data to capture all user activity within each 30-day period.
- **Key fields**: `timestamp` (current day), `joinday` (each day within the 30-day window), `hll` (daily user HLL counters)

### Component E: MAU calculation with dimensional breakdowns
- **Purpose**: Computes monthly active users across multiple dimensional cuts
- **Logic**: Merges HyperLogLog counters across each 30-day window to calculate the approximate distinct count of users. Creates four dimensional breakdowns: (1) Project-level MAU aggregating all dimensions, (2) Chain-level MAU breaking down by blockchain network, (3) User type-level MAU segmenting by user classification, and (4) Product-level MAU segmenting by protocol product. Each breakdown nullifies non-relevant dimensions while preserving the relevant grouping dimension.
- **Key fields**: `user_mau` (distinct user count from HLL extraction), `dimensions` (breakdown type), `chain_id`, `user_type`, `product_id`

### Final aggregation
- **Combining components**: All dimensional breakdowns are combined using union operations to create a comprehensive MAU dataset with multiple analytical perspectives
- **Time boundaries**: Uses 30-day rolling windows updated daily, with each day representing MAU for the preceding 30-day period
- **Schema standardization**: Applies the `finalize_metric_user_mau` macro to standardize schema structure, apply consistent formatting, and handle missing data with zero-fill strategy
- **Final calculation**: The `user_mau` field contains the final distinct user count for each dimensional breakdown and time period, calculated using HyperLogLog merge operations across the 30-day rolling window

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

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

LiquityLQTY

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown