Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Bifrost is the Staking Yield Layer app-chain for stablecoins, RWAs, and DeFi, powered by the Polkadot Relay chain.

BNC holders own and govern the protocol. Bifrost’s investors include OKX Ventures, Long Hash Ventures, etc.

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Bifrost

# Bifrost Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fee revenue generated per active user on the Bifrost network. This metric answers the business question: "How much fee revenue does each active user generate on average per day?" The calculation divides total daily fees (in USD) by the number of daily active users, providing insight into user monetization and protocol efficiency.

## 2. Data sources

The AFPU calculation relies on several raw data sources:

- **Bifrost blockchain event logs**: Parsed events from various Bifrost pallets including `vtokenMinting`, `channelCommission`, `systemStaking`, `stableAsset`, `slp`, and `transactionPayment` that capture fee-generating activities
- **Bifrost blockchain extrinsics**: Transaction records containing user addresses and transaction metadata for user identification
- **Bifrost EVM transaction logs**: Ethereum-compatible transaction events executed on Bifrost's EVM layer, identified through ethereum Executed events
- **End-of-day cryptocurrency price feeds**: External price data for tokens via Coingecko IDs to enable USD conversion
- **Token metadata**: Hardcoded mapping between Bifrost's internal token identifiers and external systems, including decimal precision and Coingecko IDs for tokens like DOT, vDOT, GLMR, vGLMR, ASTR, vASTR, FIL, vFIL, MANTA, vMANTA, and BNC

## 3. Step-by-step calculation

### Component A: Daily active users calculation
- **Purpose**: Count distinct users who performed transactions on Bifrost each day
- **Logic**: Extract user addresses from both native Bifrost extrinsics and Bifrost EVM transactions. For native transactions, the user address comes from the extrinsic `id` field. For EVM transactions, the user address is extracted from ethereum Executed event data. All users are categorized as 'Transaction sender' type. Addresses are aggregated daily using HyperLogLog to handle distinct counting across multiple dimensions including chain-level, user-type, and product-level breakdowns.
- **Key fields**: `block_timestamp` for daily aggregation, `user_address` for distinct counting, `chain` for network identification

### Component B: vToken price ratio calculation
- **Purpose**: Establish exchange rates between Bifrost's synthetic vTokens and their underlying assets
- **Logic**: Analyze `vtokenMinting.Minted` events to extract `token_amount` and `v_token_amount` values. Calculate daily average ratios by dividing token amounts by vToken amounts for each currency pair. Extract currency information from JSON event data using regex patterns to identify the token key and index. Apply forward-filling to populate missing days with the most recent available ratio.
- **Key fields**: `currency_key` and `currency_index` for token identification, `token_amount` and `v_token_amount` for ratio calculation, `vtoken_price_ratio` for the final conversion rate

### Component C: Chain-level transaction fees
- **Purpose**: Capture basic transaction processing fees paid to the Bifrost network
- **Logic**: Extract fees from `transactionPayment.TransactionFeePaid` events, combining `transaction_fee` and `transaction_tip` amounts. Convert from raw units to decimal using 12 decimal places for BNC tokens. These fees represent the cost of transaction execution on the Bifrost blockchain.
- **Key fields**: `transaction_fee` and `transaction_tip` for fee components, `extrinsic_id` for transaction linking

### Component D: Application-level fee collection
- **Purpose**: Aggregate fees from various DeFi operations across Bifrost's ecosystem
- **Logic**: Collect fees from five different sources: 1) vToken commission fees from `slp.HostingFeeCharged` events (multiplied by 10), 2) Channel commission fees from `channelCommission.ChannelClaimableCommissionUpdated` events, 3) System staking fees from `systemStaking.Payout` events, 4) Stable swap fees from `stableAsset.FeeCollected` events, and 5) Redemption fees from `vtokenMinting.Redeemed` events. For each fee type, extract currency information using regex patterns, apply token decimal conversion, and apply vToken price ratios where applicable for synthetic tokens.
- **Key fields**: Event-specific `fees` amounts, `currency_key` and `currency_index` for token identification, `coingecko_id` for price feed matching

### Component E: Token metadata mapping
- **Purpose**: Connect Bifrost's internal token system to external price feeds and standardize token handling
- **Logic**: Use hardcoded mapping table that defines relationships between Bifrost token identifiers and external systems. Map internal token IDs like 'Token2, 0' to readable names like 'DOT', specify decimal precision for each token, and provide Coingecko IDs for price feed integration. Handle both native tokens and vTokens with their respective redemption periods and conversion mechanics.
- **Key fields**: `token_id` for internal identification, `coingecko_id` for price feeds, `decimals` for unit conversion

### Final aggregation
- **Combining components**: Sum all fee types (chain-level transaction fees and application-level fees from liquid staking, channel commissions, system staking, stable swaps, and redemptions) on a daily basis. Apply vToken price ratios to synthetic token fees before USD conversion.
- **Currency conversion**: Convert all fee amounts to USD using end-of-day price feeds matched via Coingecko IDs. Apply the `convert_to_usd_cg` macro to standardize currency conversion across all fee components.
- **Time aggregation**: Truncate all timestamps to daily boundaries and aggregate fees by day. Use forward-filling for price ratios to handle missing data and zero-filling for metric gaps.
- **Final calculation**: Divide the total daily fees (in USD) by the daily active user count to produce the average fees per user. Apply the `finalize_metric_afpu` macro with zero-filling strategy for consistent time series output.

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

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Average fees per user (AFPU)

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