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

SynFutures is a non-custodial decentralized exchange for perpetual contracts built on Base and multiple EVM-based chains. SynFutures was founded by Rachel Lin and was launched in 2021. 

SynFutures’ team & investors own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). SynFutures’ investors include Polychain Capital, Framework Ventures, Pantera Capital, etc.

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SynFutures

# SynFutures Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fee revenue generated per active trader on the SynFutures perpetual trading platform. This metric is calculated by dividing total daily fees by the number of daily active users, providing insight into the revenue efficiency and user engagement of the protocol. The calculation covers all versions of SynFutures (V1, V2, V3) across multiple blockchains including Ethereum, Arbitrum, Base, Blast, BSC, and Polygon.

## 2. Data sources

- **SynFutures Trade events**: Parsed `Trade` events from perpetual futures contracts across all protocol versions, containing trader addresses, trade sizes, and prices
- **SynFutures Sweep events**: V3 `Sweep` events on Base and Blast for batch trading operations
- **Trading pair metadata**: Factory events (`NewChainlinkPair`, `NewUniswapPair`, `NewInstrument`) that establish trading pairs and their quote token addresses
- **Fee parameter events**: V3 `UpdateParam` events that track dynamic fee rate changes over time
- **End-of-day token price feeds**: Daily USD prices for quote tokens used in fee calculations
- **Token metadata**: Information about token decimals and addresses for proper conversion

## 3. Step-by-step calculation

### Component A: Trading volume extraction
- **Purpose**: Extract notional trading volumes from all SynFutures trading activities across versions and chains
- **Logic**: Parse `Trade` events from V1 (Chainlink and Uniswap pairs), V2 (WMATIC-USDC pair), and V3 (Instrument Trade/Sweep events). Extract trader addresses from `trader` or `taker` parameters, trade sizes from `size`, `takeSize`, or `entryNotional` parameters, and trade prices from `price` parameters. Convert values from wei to standard units by dividing by 1e18. Calculate notional volume as absolute value of trade size multiplied by trade price.
- **Key fields**: `trader`/`taker` addresses, `size`/`takeSize`/`entryNotional` for trade amounts, `price` for execution prices, `block_timestamp` for timing

### Component B: Trading pair metadata enrichment  
- **Purpose**: Link trade events to their corresponding quote tokens for fee calculation and price conversion
- **Logic**: Join trade events with trading pair dimensions created from Factory events. For V1, use `NewChainlinkPair` and `NewUniswapPair` events to map futures contracts to quote token addresses, handling null addresses by substituting chain native tokens. For V2, use `NewUnderlying` events to establish token mappings. For V3, use `NewInstrument` events with special price chain logic for cross-chain tokens like pumpBTC.
- **Key fields**: `futures`/`instrument` contract addresses, `quote`/`underlying` token addresses, chain-specific native token addresses

### Component C: Fee parameter tracking (V3 only)
- **Purpose**: Track dynamic fee rates that change over time in V3 protocol
- **Logic**: Process `UpdateParam` events that modify `tradingFeeRatio` and `protocolFeeRatio` parameters. Create time intervals between parameter changes, filtering out irrelevant updates where fees remain unchanged. Establish valid time ranges for each fee configuration to apply correct rates to trade events based on timestamp.
- **Key fields**: `tradingFeeRatio` and `protocolFeeRatio` basis points, `block_timestamp` for timing, instrument addresses for scope

### Component D: Fee calculation
- **Purpose**: Calculate total fees generated from trading activity using version-specific methodologies
- **Logic**: Apply different fee calculation methods by protocol version. V1 uses hardcoded rates: 0.25% for supply-side fees, and protocol fees of 0.05% before September 29, 2021, then 0.01% afterward. V2 uses explicit `tradingFee` and `reserveFee` values from trade events, converting from wei. V3 multiplies notional volume by dynamic `tradingFeeRatio` and `protocolFeeRatio` basis points divided by 10,000. Combine supply-side and protocol fees for total fee amount.
- **Key fields**: Notional volumes, hardcoded fee percentages (V1), explicit `tradingFee`/`reserveFee` (V2), dynamic basis points (V3)

### Component E: USD conversion
- **Purpose**: Convert all fee amounts to USD for consistent measurement
- **Logic**: Join calculated fees with end-of-day token price feeds using quote token addresses and daily timestamps. For V3, handle cross-chain pricing by using the appropriate price chain (e.g., Ethereum prices for pumpBTC on Base). Apply price conversion to get fee values in USD.
- **Key fields**: Quote token addresses, daily price feeds, chain specifications for pricing

### Component F: Daily active user counting
- **Purpose**: Count unique traders per day across all trading activities
- **Logic**: Extract trader addresses from the same Trade events used for fee calculation. Use `trader` parameter for V1/V3 and `taker` parameter for V2. Group by daily timestamps and count distinct addresses using HyperLogLog aggregation for efficient computation. Aggregate across all chains and protocol versions to get total daily active users.
- **Key fields**: Trader addresses, daily timestamps, user type classifications

### Final aggregation
- **Combining components**: Sum all daily fees (supply-side plus protocol fees) across all protocol versions and chains to get total daily fee revenue. Sum daily active users across all versions and chains to get total daily active users.
- **Currency conversion**: All fees are converted to USD using end-of-day token prices matched by quote token address and daily timestamp
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with consistent daily grouping across fees and user metrics
- **Final calculation**: AFPU equals total daily fees in USD divided by total daily active users, with zero-filling applied for days with no trading activity to maintain complete time series

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

SynFuturesF

Average fees per user (AFPU)

Average fees per user (AFPU)

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