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Blockchains (L3)

# XAI Median transaction fee Methodology

## 1. Overview

The XAI transaction fee median metric measures the middle value (50th percentile) of transaction fees on the XAI blockchain, expressed in USD. This metric helps analyze the typical cost that users pay for transactions on the XAI Layer 3 blockchain, providing insight into network usage costs and accessibility. The calculation aggregates daily transaction data to compute median gas fees in native XAI tokens, then converts these values to USD using end-of-day XAI token prices.

## 2. Data sources

- **XAI blockchain transaction records**: Raw transaction data from the XAI blockchain containing transaction hashes, gas usage amounts (`receipt_gas_used`), effective gas prices (`receipt_effective_gas_price`), sender and receiver addresses, and block timestamps
- **End-of-day price feeds**: Daily XAI token price data from CoinGecko using the `xai-blockchain` identifier, providing USD price conversions for the native XAI token

## 3. Step-by-step calculation

### Component A: Transaction gas fee calculation
- **Purpose**: Extract individual transaction fees from raw XAI blockchain data
- **Logic**: Retrieves all transactions from XAI blockchain records, filtering for transactions up to the specified cutoff date. For each transaction, calculates the L3 gas fee by multiplying the `gas_used_amount` (from `receipt_gas_used`) by the `gas_price` (from `receipt_effective_gas_price`). Converts the result from wei to XAI tokens by dividing by 1e18. Handles null gas fee amounts by defaulting to zero using coalesce function.
- **Key fields**: `block_timestamp` for temporal grouping, `l3_gas_fee_amount` as the calculated fee in XAI tokens, `transaction_hash` for transaction identification

### Component B: Daily median aggregation
- **Purpose**: Calculate the median transaction fee for each day
- **Logic**: Groups transaction fee data by day using timestamp truncation to daily boundaries. Applies approximate quantiles calculation using the 50th percentile (median) across all transaction fees within each day. Uses `approx_quantiles(fee_amount, 100)[offset(50)]` to efficiently compute the median value from potentially large transaction volumes.
- **Key fields**: `timestamp` as the daily date boundary, `transaction_fee_median` as the median fee amount in XAI tokens

### Component C: Price data integration
- **Purpose**: Retrieve daily XAI token prices for USD conversion
- **Logic**: Extracts end-of-day XAI token prices from CoinGecko daily market data using the `xai-blockchain` identifier. Filters price data to match the same date range as transaction data, ensuring consistent temporal alignment.
- **Key fields**: `timestamp` for date matching, `price` as the USD value per XAI token

### Final aggregation
- **Combining components**: Joins daily median transaction fees with corresponding daily XAI token prices on the timestamp field using an inner join to ensure both fee and price data are available
- **Currency conversion**: Multiplies the median transaction fee (in XAI tokens) by the daily XAI token price to get the USD-denominated median fee
- **Time aggregation**: Data is aggregated to daily boundaries with the `timestamp_grain` field set to 'day'
- **Final calculation**: The final metric value is the product of `transaction_fee_median` from the median calculation and `price` from the price feed, representing the median transaction fee in USD for each day. Additional metadata fields are populated including `chain_id` as 'xai', `token_address` using a WETH address variable, and `product_id` as null. A fill zeros strategy is applied to handle missing data points, and chain availability filtering ensures data quality.

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

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