The option buyers pay premiums (revenue) to HEGIC stakers, who collateralize the option positions and cover the buyers' potential profits from their collateral.

Hegic is a non-custodial options exchange built on Arbitrum. Hegic was founded by Molly Wintermute and launched in 2020.



HEGIC tokenholders own and govern the protocol. They charge a premium (revenue) for each option that is bought on the platform.

github

twitter

discord

etherscan

website

Derivative exchanges

Hegic

# Hegic Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) for Hegic measures the average daily revenue generated per active user on the decentralized options trading protocol. This metric answers the business question: "How much revenue does each active user generate on average per day?" The calculation divides daily trading fee revenue by the number of daily active users, providing insight into user monetization and platform efficiency.

## 2. Data sources

- **Arbitrum event logs**: Parsed `PositionsManager_Transfer_event` logs capturing option position transfers and minting activities
- **Strategy acquisition events**: Parsed `HegicStrategyCall_Acquired_event` logs linking position transfers to specific option strategies  
- **Treasury payment events**: Parsed `OperationalTreasury_Paid_event` logs recording option exercise settlements
- **Token transfer data**: Arbitrum USDC token transfer records linked to option trading activities
- **End-of-day price feeds**: USDC to USD conversion rates for revenue calculation
- **Strategy metadata**: Hardcoded dimension mappings for option strategy classification (call/put options, spreads, straddles, etc.)

## 3. Step-by-step calculation

### Component A: Revenue calculation
- **Purpose**: Calculate daily revenue from option trading fees in USD
- **Logic**: Extract USDC token transfers that occur when users mint new option positions. Filter `PositionsManager_Transfer_event` logs where the `from` field equals the null address, indicating new position creation rather than secondary transfers. Join these events with corresponding USDC token transfers using transaction hash matching. Link position transfers to `HegicStrategyCall_Acquired_event` logs to identify the specific option strategy being purchased. Convert USDC amounts to USD using end-of-day price feeds and apply decimal correction for USDC's 6-decimal precision. Aggregate daily by chain, product segments, and business categories.
- **Key fields**: `block_timestamp` for daily aggregation, `value` from token transfers for fee amounts, `token_address` filtered to USDC contract, `transaction_hash` for event linking

### Component B: Daily active users calculation  
- **Purpose**: Count unique users interacting with the protocol each day
- **Logic**: Identify two types of users from Arbitrum event logs. Option Buyers are captured from `PositionsManager_Transfer_event` logs where the `to` field receives a newly minted position (when `from` equals null address). Option Exercisers are identified from `OperationalTreasury_Paid_event` logs where the `account` field receives settlement payments. Extract user addresses and timestamps, then deduplicate using HyperLogLog aggregation to count unique users per day across multiple dimensions including overall project level, individual chains, user types, and product categories.
- **Key fields**: `user_address` for deduplication, `block_timestamp` for daily boundaries, `user_type` for buyer/exerciser classification, `chain` for network identification

### Final aggregation
- **Combining components**: Join daily revenue totals with daily active user counts by matching on date, chain, and dimensional breakdowns
- **Currency conversion**: Revenue amounts are converted from USDC to USD using end-of-day price feeds with proper decimal adjustment for 6-decimal USDC precision  
- **Time aggregation**: All events are aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: Divide total daily revenue by total daily active users to produce average revenue per user, with proper handling of division by zero scenarios and application of zero-filling for missing date ranges

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

HegicHEGIC

Average revenue per user (ARPU)

Average revenue per user (ARPU)

Competitive landscape