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.

governance

github

twitter

discord

etherscan

website

Derivative exchanges

Perpetual Protocol

# Perpetual Protocol Supply-side fees Methodology

## 1. Overview

Supply-side fees represent the portion of trading and liquidation fees that go to liquidity providers and liquidators on Perpetual Protocol rather than to the protocol itself as revenue. This metric tracks the value distributed to the supply side of the market across both v1 (on Gnosis Chain) and v2 (on Optimism) implementations. The calculation applies different fee splitting logic based on protocol version and fee type (trading vs liquidation).

## 2. Data sources

- **Smart contract events**: Parsed `PositionChanged` events from Perpetual Protocol ClearingHouse contracts on Gnosis Chain (v1) and Optimism (v2) containing trading fee data
- **Smart contract events**: Parsed `PositionLiquidated` events from Perpetual Protocol ClearingHouse contracts on Gnosis Chain (v1) and Optimism (v2) containing liquidation fee data  
- **Market configuration**: Protocol-maintained mapping of market contract addresses to token symbols for both v1 and v2 markets
- **Revenue parameters**: Time-based configuration defining the revenue percentage split that determines how much of trading fees goes to the protocol versus liquidity providers
- **Price feeds**: End-of-day token price feeds for converting native token amounts to USD values
- **Token metadata**: Token address mappings for xDAI on Gnosis Chain and USDC on Optimism

## 3. Step-by-step calculation

### Component A: Trading fee extraction
- **Purpose**: Extract trading fees from position change events across both protocol versions
- **Logic**: Query parsed `PositionChanged` events from ClearingHouse contracts on both Gnosis Chain (v1) and Optimism (v2). Extract the `fee` field from each event, convert from 18-decimal precision to standard format by dividing by 10^18, and label as 'Trading' component. Map chain-specific settlement tokens (xDAI for v1, USDC for v2) and capture market addresses (`amm` field for v1, `baseToken` for v2)
- **Key fields**: `fee` amount, `amm`/`baseToken` market address, transaction metadata, account addresses

### Component B: Liquidation fee extraction  
- **Purpose**: Extract liquidation fees from liquidation events across both protocol versions
- **Logic**: Query parsed `PositionLiquidated` events from ClearingHouse contracts on both chains. Extract the `liquidationFee` field, convert from 18-decimal precision, and label as 'Liquidation' component. Use same chain-specific token mapping and market address extraction as trading fees
- **Key fields**: `liquidationFee` amount, market addresses, transaction metadata, account addresses

### Component C: Market classification
- **Purpose**: Map market contract addresses to human-readable token symbols
- **Logic**: Join fee events with market dimension table using market address as the key. This maps contract addresses to token symbols like 'vBTC', 'vETH', 'ETHUSDC', etc. Unknown markets get labeled as 'Unknown' to handle new markets not yet in the configuration
- **Key fields**: Market contract addresses mapped to `token_symbol` and `contract_name`

### Component D: USD conversion and temporal aggregation
- **Purpose**: Convert native token amounts to USD and aggregate to daily boundaries
- **Logic**: Join fee data with end-of-day price feeds to convert token amounts to USD values. Truncate timestamps to daily boundaries and group by day, chain, market, and fee component. Apply decimal correction and currency conversion through standard macro processing
- **Key fields**: Daily `timestamp`, USD-converted `fees`, aggregation dimensions

### Component E: Revenue percentage application
- **Purpose**: Join with time-based revenue sharing configuration to determine supply-side portion
- **Logic**: Join aggregated fee data with revenue percentage dimension table by timestamp. This table contains the protocol's revenue percentage that changed over time (10% from 2021-11-25, increased to 20% from 2022-06-22). Values are forward-filled to cover all dates
- **Key fields**: `revenue_percentage` applied to determine supply-side split

### Final aggregation
- **Combining components**: Apply version and component-specific business logic through case statements: v1 trading fees get 0% supply-side allocation (all fees go to protocol), v1 liquidation fees get 100% supply-side allocation (all go to liquidators), v2 liquidation fees get 100% supply-side allocation, and v2 trading fees get (1 - revenue_percentage) supply-side allocation based on the time-varying split
- **Currency conversion**: All amounts converted to USD using end-of-day price feeds matched to the transaction date
- **Time aggregation**: Events aggregated to daily boundaries with daily timestamp grain
- **Final calculation**: Supply-side fees equal the original fee amount multiplied by the appropriate supply-side percentage based on version, component type, and time period, with results filtered by chain availability constraints

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

Portion of fees distributed to service providers or supply-side participants.

Perpetual ProtocolPERP

Supply-side fees

Supply-side fees

Competitive landscape

Chain breakdown