Liquidity providers deposit funds into Thetanuts and receive option premiums from traders (supply-side fees).

Thetanuts is a non-custodial DeFi Options Vault (DOV) protocol built on Ethereum, Fantom, Polygon, and other blockchains. Thetanuts was founded by Dexter Song and launched in Dec 2021.

Thetanuts team own and govern the protocol. Their investors include Deribit Exchange, QCP Capital, Jump Crypto, etc.

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Asset management

Thetanuts

# Thetanuts Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique users who interact with Thetanuts protocol within any 30-day period. This metric answers the business question of user engagement and growth by tracking distinct wallet addresses that perform deposit or withdrawal operations across Thetanuts' covered call vault contracts. The calculation uses HyperLogLog probabilistic counting to efficiently compute unique users across rolling 30-day windows, providing dimensional breakdowns by blockchain, user activity type, and product.

## 2. Data sources

- **Blockchain events**: Parsed `Deposit` and `Withdraw` events from Thetanuts CoveredCall smart contracts across six blockchains (Ethereum, Arbitrum, Avalanche, BSC, Fantom, and Polygon)
- **Event parameters**: User wallet addresses from event parameters (`from` field for both deposit and withdrawal events)  
- **Transaction metadata**: Block timestamps, transaction hashes, and log indices from blockchain transaction records
- **Chain data**: Blockchain identifier information for multi-chain aggregation

## 3. Step-by-step calculation

### Component A: User interaction extraction
- **Purpose**: Identifies all unique user interactions with Thetanuts protocol contracts
- **Logic**: Extracts user addresses from parsed blockchain events across six chains. For each chain, the system collects `Deposit` events (capturing depositor addresses) and `Withdraw` events (capturing withdrawer addresses) from the respective CoveredCall contracts. Each interaction includes the user address, timestamp, transaction details, and is classified by user type (Depositor or Withdrawer). All interactions are tagged with market sector as asset management and business segment as yield aggregator.
- **Key fields**: User addresses are extracted from the `from` parameter, block timestamps provide timing data, and chain identifiers enable multi-chain aggregation

### Component B: Daily active user aggregation  
- **Purpose**: Creates daily snapshots of unique active users with dimensional attributes
- **Logic**: Groups user interactions by calendar day using timestamp truncation to daily boundaries. For each day, collects all unique user addresses that performed any interaction, preserving dimensional information including blockchain, user type classification, market sector, business segment, and product identifiers. This creates a daily unique user dataset that serves as the foundation for monthly calculations.
- **Key fields**: Daily `timestamp` boundaries, unique `user_address` values per day, `chain` identifiers, `user_type` classifications, and `product_id` information

### Component C: HyperLogLog sketch creation
- **Purpose**: Converts daily user sets into probabilistic data structures for efficient monthly aggregation
- **Logic**: Transforms each day's unique user address list into HyperLogLog sketches with precision parameter 15. This probabilistic approach enables efficient union operations across multiple days without storing complete user address lists. Each daily sketch represents the set of unique users for that specific day while maintaining dimensional groupings.
- **Key fields**: HyperLogLog `hll` sketches initialized from daily user address sets, preserving all dimensional attributes

### Component D: 30-day rolling window construction
- **Purpose**: Creates overlapping monthly periods for each calendar day
- **Logic**: Generates a complete datespine covering the full analysis period, then for each calendar day, identifies the corresponding 30-day window (including the current day and 29 preceding days). Uses array generation to create day-by-day mapping between target dates and their constituent daily periods. This ensures every day has a complete 30-day lookback window for monthly user counting.
- **Key fields**: Target `timestamp` for each monthly calculation and corresponding `joinday` timestamps for the 30-day constituent period

### Component E: Monthly user aggregation
- **Purpose**: Calculates unique users across 30-day rolling windows using HyperLogLog unions
- **Logic**: For each target date and its 30-day window, merges all daily HyperLogLog sketches using HLL union operations. This efficiently counts unique users who were active at any point during the 30-day period without double-counting users who were active on multiple days. Maintains all dimensional breakdowns throughout the aggregation process.
- **Key fields**: Merged HyperLogLog sketches representing unique users across 30-day windows, dimensional groupings preserved

### Component F: Dimensional breakdown calculation
- **Purpose**: Provides MAU metrics across four different dimensional perspectives
- **Logic**: Creates separate aggregations for project-level (overall Thetanuts MAU), chain-level (MAU per blockchain), user-type-level (MAU for depositors versus withdrawers), and product-level (MAU per product) metrics. Each breakdown extracts unique user counts from the merged HyperLogLog sketches while setting non-applicable dimensional fields to null. All breakdowns are combined into a single dataset with a dimensions identifier.
- **Key fields**: Extracted `user_mau` counts from HyperLogLog sketches, `dimensions` type identifier, and relevant dimensional values (`chain_id`, `user_type`, `product_id`)

### Final aggregation
- **Combining components**: Union all dimensional breakdowns into a comprehensive dataset containing MAU values across all dimensional perspectives
- **Schema standardization**: Apply consistent column naming, data types, and metadata using the finalize metric macro
- **Missing data handling**: Fill gaps in the time series with zero values for dates without user activity
- **Final calculation**: The final MAU value represents the count of unique wallet addresses that performed at least one deposit or withdrawal operation within any given 30-day rolling period, calculated using HyperLogLog approximate counting for scalability across large user bases and multiple blockchains

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

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

Thetanuts

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown