Liquidity providers deposit funds into Perpetual Protocol to earn a share of trading fees (supply-side fees). Perpetual Protocol leverages Uniswap v3's architecture as a pricing engine, enabling traders to access up to 10x leverage. Perpetual Protocol also offers Hot Tub vaults, which operate trading strategies that generate yield from arbitrage profits. 

Perpetual Protocol is an open-source and non-custodial exchange for perpetual contracts built on Optimism. Perpetual Protocol was founded by Shao-Kang Lee & Yenwen Feng and launched in 2019.

PERP token holders own and govern the protocol. Token holders can boost their governance power and earn 15% of trading fees paid by traders (revenue) by locking PERP into vote-escrowed PERP (vePERP). Perpetual Protocol's investors include CMS Holdings, Binance Labs, and Mechanism Capital.

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Derivative exchanges

Perpetual Protocol

# Perpetual Protocol Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who actively trade on Perpetual Protocol during any 7-day period. This metric tracks user engagement across the protocol's derivatives trading platform deployed on multiple blockchain networks. The calculation uses a rolling 7-day window approach with HyperLogLog probabilistic counting to efficiently handle large user datasets while providing accurate distinct user counts across different dimensional breakdowns.

## 2. Data sources

- **Blockchain events**: Parsed `PositionChanged` events from Perpetual Protocol's ClearingHouse contracts on Gnosis and Optimism networks
- **Contract data**: Perpetual Protocol v1 contract events on Gnosis chain and v2 contract events on Optimism chain
- **Event parameters**: Trader addresses extracted from position change events that indicate active trading activity

## 3. Step-by-step calculation

### Component A: User identification and classification
- **Purpose**: Identifies and classifies active traders from blockchain events
- **Logic**: Extracts user addresses from `PositionChanged` events emitted by ClearingHouse contracts when users modify their trading positions. Events are sourced from Perpetual Protocol v1 contracts on Gnosis chain and v2 contracts on Optimism chain. Each trader address from the `trader` parameter is classified as 'Trader' user type within the 'derivatives' market sector and 'perpetualprotocol' business segment
- **Key fields**: `trader` addresses from position events, `block_timestamp` for timing, `chain` identifier for network classification

### Component B: Daily active user aggregation  
- **Purpose**: Aggregates unique users by calendar day to create daily active user baseline
- **Logic**: Takes the identified trader addresses and groups them by calendar day using timestamp truncation to daily boundaries. Creates distinct user counts for each day while maintaining dimensional breakdowns by chain, user type, and product. Applies chain availability filtering to ensure data quality and completeness
- **Key fields**: `timestamp` truncated to day level, `user_address` for uniqueness, dimensional attributes for breakdowns

### Component C: Weekly window creation
- **Purpose**: Creates 7-day rolling windows for weekly active user calculation
- **Logic**: Generates a complete datespine covering all days from the first recorded activity through yesterday to ensure no gaps in the time series. For each day in the datespine, creates a 7-day lookback window consisting of the current day plus the previous 6 days. This approach ensures every day has a complete weekly context for user activity measurement
- **Key fields**: `timestamp` for window boundaries, `joinday` for daily components within each weekly window

### Component D: HyperLogLog probabilistic counting
- **Purpose**: Efficiently counts distinct users across weekly periods while handling large datasets
- **Logic**: Initializes HyperLogLog sketches for each daily active user count with 15-bit precision for memory efficiency. HyperLogLog enables approximate distinct counting without storing individual user addresses, making it scalable for high-volume user data. Each daily user set is converted into an HLL sketch that can be merged with other sketches
- **Key fields**: `hll` sketches containing probabilistic representations of daily user sets

### Final aggregation
- **Combining components**: Joins the weekly window datespine with daily HLL sketches to create complete 7-day user activity windows. Merges HyperLogLog sketches across the 7-day periods using HLL merge operations to combine user sets while preventing double-counting of users who are active on multiple days within the same week
- **Currency conversion**: Not applicable - this metric counts users, not monetary values  
- **Time aggregation**: Uses rolling 7-day windows where each day represents the WAU for that day's weekly period (current day plus previous 6 days). No fixed weekly boundaries - each day gets its own weekly calculation
- **Final calculation**: Extracts final distinct user counts from the merged HyperLogLog sketches using HLL count extraction. Creates four dimensional breakdowns: project-level aggregation combining all chains and dimensions, chain-level breakdown showing WAU per blockchain network, user-type-level breakdown (currently only 'Trader' type), and product-level breakdown for future product segmentation. All breakdowns are combined into a unified result set with appropriate dimensional flags and null values for non-applicable dimensions.

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

Unique revenue-generating users over a rolling 7-day window.

Perpetual ProtocolPERP

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown