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

Thruster is a non-custodial exchange protocol built on Blast. Thruster was launched in 2024.

Thruster team and investors own and govern the protocol. They currently take a cut of the total trading fees paid by traders, and earn native yield (revenue). Thruster's investors include Mirana Ventures, Manifold, OKX Ventures, etc.

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Thruster

# Thruster Average trading volume (per user) Methodology

## 1. Overview

Trading volume average per user measures the average daily trading volume per daily active user on the Thruster decentralized exchange protocol. This metric provides insights into user engagement depth by dividing total daily trading volume (in USD) by the number of unique daily active users. It helps assess how actively engaged users are in terms of trading activity volume, indicating both user behavior patterns and the protocol's trading intensity per participant.

## 2. Data sources

- **Blast blockchain Swap events**: Parsed `Swap` events from Thruster classic (v2) AMM pairs and CLAMM (v3) concentrated liquidity pools, containing token amounts and user addresses
- **Blast blockchain Flash loan events**: Parsed `Flash` events from Thruster pools for additional user activity tracking
- **Blast transaction records**: Transaction data providing user addresses (`from_address`) for all trading and flash loan activities
- **Thruster factory events**: `PairCreated` and `PoolCreated` events from factory contracts identifying trading pairs and their token addresses
- **Protocol fee events**: `SetYieldCut` events tracking protocol fee tier changes over time
- **End-of-day price feeds**: Token price data for USD conversion of trading volumes
- **Token metadata**: Token information including decimal places and symbols for proper amount calculations

## 3. Step-by-step calculation

### Component A: Raw trade event collection
- **Purpose**: Collect all swap transactions from Thruster exchange protocols
- **Logic**: Extract `Swap` events from both Thruster classic v2 pairs (`Pair03_Swap_event`, `Pair1_Swap_event`) and CLAMM v3 pools (`Pool_Swap_event`) on the Blast blockchain. For classic pairs, calculate net token amounts by subtracting `amount0Out` from `amount0In` and `amount1Out` from `amount1In`. For CLAMM pools, use direct `amount0` and `amount1` values. Join with Blast transaction records to identify the actual user address (`from_address`) rather than just the contract caller address
- **Key fields**: `block_timestamp`, `transaction_hash`, `account_address` (pool/pair contract), `user_address` (transaction initiator), `token0_amount`, `token1_amount`, `product_id` (thrusterclassic vs thrusterclamm)

### Component B: Trading pair metadata enrichment
- **Purpose**: Add token metadata and fee information to trades
- **Logic**: Join trade events with trading pair data derived from factory `PairCreated` and `PoolCreated` events. This provides token addresses, decimal places for both tokens in each pair, and fee tiers. Apply exclusion filters to remove denylisted trading pairs. Correct token amounts by dividing by 10 raised to the power of each token's decimal places to get actual token quantities
- **Key fields**: `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `fee_tier`, corrected `token0_amount`, `token1_amount`

### Component C: Protocol fee tier calculation
- **Purpose**: Determine protocol fee rates for revenue calculations
- **Logic**: Join with protocol fee update events (`SetYieldCut`) and apply time-based logic. For transactions after April 10, 2024, 04:58:19 UTC (fee switch activation), use the configured protocol fee tier or default to 0.5 if none specified. For transactions before this timestamp, use the configured fee tier or default to 0 (no protocol fees). Use forward-filling to apply fee rates across time periods until the next update
- **Key fields**: `protocol_fee_tier`, `timestamp` for fee switch logic

### Component D: USD conversion with price manipulation protection
- **Purpose**: Convert token amounts to USD values while filtering out manipulated prices
- **Logic**: Join corrected token amounts with end-of-day price feeds for both tokens in each trading pair. Calculate USD values by multiplying token amounts by their respective prices. Apply price manipulation protection by taking the minimum (least) USD value between the two tokens in the pair - this filters out trades where one token's price appears manipulated relative to the other. Sum the resulting USD values daily to get total trading volume
- **Key fields**: `trading_volume` (daily USD amount), `timestamp` (daily grain)

### Component E: Flash loan user activity tracking
- **Purpose**: Capture additional user activity beyond just trading
- **Logic**: Extract `Flash` events from Thruster pools and join with transaction records to identify users. This ensures users who interact with the protocol through flash loans (but may not trade in the same transaction) are counted in daily active user calculations
- **Key fields**: `user_address`, `block_timestamp`, `chain_id`

### Component F: Daily active user calculation
- **Purpose**: Count unique daily users across all protocol activities
- **Logic**: Combine user addresses from both trading activities (swap events) and flash loan activities, truncated to daily timestamps. Use HyperLogLog (HLL) data structure with precision 15 for efficient distinct counting across large datasets. Aggregate users at the project level (across all products and chains) to get overall protocol daily active users
- **Key fields**: `user_dau` (distinct user count), `timestamp` (daily), `dimensions` ('project_dbt_tag' for overall project aggregation)

### Final aggregation
- **Combining components**: Join daily trading volume data with daily active user data by matching timestamps. Use an inner join to ensure both metrics exist for the same day
- **Currency conversion**: Trading volume is already converted to USD in the volume calculation pipeline using end-of-day token prices
- **Time aggregation**: Both components use daily timestamp boundaries (truncated to day) for consistent aggregation
- **Final calculation**: Calculate the average trading volume per user using `safe_divide(trading_volume, user_dau)` to handle edge cases where daily active users might be zero, preventing division errors. The result represents the average USD trading volume per daily active user for each day

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

Average trading volume (per user)

Trading volume divided by daily active users.

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Average trading volume (per user)

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