Validators process transactions and receive fees from users (supply-side fees).

Aptos is a smart contract platform for decentralized applications (a blockchain). Aptos was founded by Mo Shaikh and Avery Ching and launched in 2022.

APT token holders own and govern the protocol. They currently don’t take a cut of the total transaction fees paid by users (revenue). Aptos’ investors include Binance Labs, Jump Crypto, Apollo, etc.

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Aptos

# Aptos Average transaction fee Methodology

## 1. Overview

The average transaction fee metric measures the mean cost per transaction on the Aptos blockchain, denominated in USD. This metric helps assess the economic efficiency and cost-effectiveness of using the Aptos network by calculating the ratio of total daily transaction fees to total daily transaction count.

## 2. Data sources

- **Aptos blockchain transaction data**: Complete transaction records including gas usage, gas unit prices, block timestamps, transaction hashes, and sender addresses
- **Chainlink price feeds**: End-of-day APT/USD price data from August 10, 2023 onwards using feed address `0x88a98431c25329aa422b21d147c1518b34dd36f4`
- **CoinGecko market data**: Daily APT token price data in USD for periods before Chainlink feed availability (pre-August 2023)

## 3. Step-by-step calculation

### Component A: Transaction fee calculation
- **Purpose**: Calculate individual transaction fees in native APT tokens and convert to USD
- **Logic**: Extract all Aptos transactions including gas usage and gas unit price data. Calculate individual transaction fees by multiplying `gas_used` by `gas_unit_price`, where gas unit price is converted from octa units by dividing by 10^8. Handle genesis transactions by hardcoding timestamps before 2000-01-01 to October 12, 2022. Aggregate fees daily by summing all transaction fee amounts per day. Convert APT-denominated fees to USD by joining with price data - using Chainlink feeds for dates from August 10, 2023 onwards and CoinGecko data for earlier periods.
- **Key fields**: `gas_used`, `gas_unit_price` (converted from octa), `block_timestamp`, `fee_amount` (in APT), `fees` (in USD)

### Component B: Transaction count calculation  
- **Purpose**: Count unique transactions per day on Aptos blockchain
- **Logic**: Process all Aptos transaction records and count distinct transactions daily using `transaction_hash` as the unique identifier. Apply timestamp truncation to daily boundaries and group transactions by day. Use distinct counting to avoid duplicate transactions that might appear multiple times in the raw data.
- **Key fields**: `transaction_hash`, `block_timestamp`, `transaction_count`

### Component C: Price data integration
- **Purpose**: Provide APT/USD exchange rates for fee conversion
- **Logic**: Combine two price data sources with date-based selection. Use Chainlink price feeds for dates on or after August 10, 2023, filtering by the specific APT feed address. For earlier dates, use CoinGecko daily market data for the APT token, casting price values to appropriate numeric types. Union the two datasets to create a complete price history.
- **Key fields**: `timestamp`, `price` (APT/USD exchange rate)

### Final aggregation
- **Combining components**: Join the daily fee totals (in USD) with daily transaction counts on matching timestamps using inner join to ensure both metrics exist for the calculation date
- **Currency conversion**: Fees are converted to USD using end-of-day APT prices, with Chainlink data taking precedence over CoinGecko for overlapping periods
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation, with consistent daily timestamp alignment across all components  
- **Final calculation**: Calculate average transaction fee by dividing total daily fees in USD by total daily transaction count using safe division to handle potential zero-transaction days, resulting in the mean transaction cost per day

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

AptosAPT

Average transaction fee

Average transaction fee

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