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

Aperture is a non-custodial DeFi exchange protocol built on Manta Pacific (originally a fork of Uniswap). Aperture was founded by Gao Han, Lian Zhu, and Peiqian Li in 2021.

Aperture team & investors own and govern the protocol. They do not currently take a cut of the total trading fees paid by traders (revenue). Aperture's investors include ParaFi Capital, Arrington XRP Capital, Costanoa Ventures and Divergence Ventures.

github

twitter

discord

website

Exchanges (DEX)

Aperture

# Aperture Trade count Methodology

## 1. Overview

The Aperture trade count metric measures the daily number of unique trades executed on the Aperture decentralized exchange. This metric counts distinct transactions containing swap events, providing insight into trading activity and user engagement on the platform. The calculation aggregates swap transactions by day and applies business taxonomy classifications to categorize the trades within Token Terminal's framework.

## 2. Data sources

The calculation relies on several raw data sources from the Manta Pacific blockchain:

- **Swap events**: Parsed `Pool_Swap_event` logs from Aperture V1 pool contracts containing swap transaction details, token amounts, user addresses, and pool information
- **Pool creation events**: `PoolCreated` events from Aperture Factory contracts that establish trading pairs with token addresses and fee tier configurations  
- **Transaction records**: Manta Pacific transaction data providing user addresses and transaction metadata
- **Token metadata**: Token registry data containing symbol names and decimal place specifications for amount normalization
- **End-of-day price feeds**: Daily USD price data for tokens to enable volume-based filtering and validation

## 3. Step-by-step calculation

### Component A: Raw trade event extraction
- **Purpose**: Extract and process raw swap events from Aperture pool contracts
- **Logic**: Collect all `Pool_Swap_event` logs from Aperture V1 pool contracts on Manta Pacific. Each event captures a swap transaction with details including the pool address, transaction hash, log index, sender address, and the amounts of both tokens involved in the swap (`amount0` and `amount1` fields). Join with transaction records to obtain the originating user address (`from_address`) for each swap
- **Key fields**: `transaction_hash` for trade identification, `log_index` for event ordering, `account_address` for the pool contract, `amount0` and `amount1` for token quantities, and user addresses for attribution

### Component B: Trading pair metadata enrichment  
- **Purpose**: Enhance trade data with trading pair information and token metadata
- **Logic**: Join swap events with Factory `PoolCreated` events to retrieve trading pair details including `token0_address`, `token1_address`, and `fee_tier` information. Further join with token metadata to obtain decimal specifications and symbol names for each token in the pair. Create human-readable account names by concatenating token symbols (e.g., "ETH-USDC")
- **Key fields**: `token0_address` and `token1_address` for token identification, `token0_decimals` and `token1_decimals` for amount correction, `account_name` for pair identification, and `fee_tier` for pool classification

### Component C: Volume calculation and validation
- **Purpose**: Process token amounts and apply volume-based filtering to exclude potential price manipulation
- **Logic**: Aggregate trades by day and correct token amounts by dividing by the appropriate decimal factor (10^decimals). Convert both token amounts to USD values using end-of-day price feeds. Apply price manipulation filtering by taking the lesser USD value between the two tokens in each swap, ensuring that trades with suspicious price discrepancies are properly handled. This USD conversion serves as validation but does not directly impact the final trade count
- **Key fields**: `token0_amount` and `token1_amount` after decimal correction, `trading_volume` as the lesser USD value between token pairs

### Final aggregation
- **Combining components**: Aggregate the processed trade data at the daily level, grouping by timestamp, chain, market sector, business segment, and product identifiers
- **Currency conversion**: While USD conversion is performed for validation purposes, the final metric counts transactions rather than measuring monetary values
- **Time aggregation**: Trades are aggregated using daily boundaries based on `timestamp_trunc(block_timestamp, day)` to establish consistent daily periods
- **Final calculation**: Count distinct `transaction_hash` values per day to determine the number of unique trading transactions. This approach ensures that multiple swap events within a single transaction are counted as one trade. Apply the `finalize_metric_trade_count` macro with zero-filling strategy to ensure consistent daily reporting and include chain availability filtering to respect data availability windows

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

Number of trades executed on a decentralized exchange.

Aperture

Trade count

Trade count

Competitive landscape

Chain breakdown