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 Token incentives Methodology

## 1. Overview

The Aperture token incentives metric represents the USD value of token-based incentives distributed by the Aperture protocol to users and liquidity providers. This metric answers the business question: "How much does Aperture spend on token incentives to encourage platform usage?" Currently, Aperture does not distribute any token incentives, so this metric is consistently set to 0. The calculation reuses the structural framework from the fees metric to maintain consistent time series data while setting all incentive values to zero.

## 2. Data sources

The metric leverages the same data infrastructure as the fees calculation to maintain structural consistency:

- **Manta blockchain events**: Parsed Aperture protocol events including `Pool_Swap_event`, `Pool_Flash_event`, and `Factory_PoolCreated_event` logs
- **Transaction data**: Manta blockchain transaction records for user address identification and transaction context
- **Token metadata**: Token symbols, decimal places, and identifiers for proper data processing
- **End-of-day price feeds**: Token price data in USD for structural consistency (though not used for the actual zero calculation)

Note: While these data sources provide the structural framework, the actual token incentives values are hardcoded to 0 since Aperture currently does not distribute token-based incentives.

## 3. Step-by-step calculation

### Component A: Structural framework extraction
- **Purpose**: Extracts the time series structure and identifiers needed for the token incentives metric
- **Logic**: Uses the `aperture_metrics_fees` model as a structural template, selecting key fields including `timestamp`, `timestamp_grain`, `product_id`, and `chain_id`. This ensures the token incentives metric aligns with the same time boundaries and chain/product identifiers as other Aperture metrics
- **Key fields**: `timestamp` (daily boundaries), `timestamp_grain` (set to 'day'), `product_id` (aperture identifier), `chain_id` (manta)

### Component B: Zero value assignment
- **Purpose**: Sets all token incentives values to zero
- **Logic**: Creates a computed column `token_incentives` with a hardcoded value of 0 for all records. This reflects the current reality that Aperture does not distribute token-based incentives to users or liquidity providers
- **Key fields**: `token_incentives` (always 0)

### Final aggregation
- **Combining components**: The structural framework and zero values are combined in a single query, creating a complete time series with consistent zero values
- **Currency conversion**: Not applicable since values are hardcoded to 0, though USD is the standard currency for consistency
- **Time aggregation**: Daily time boundaries are maintained from the fees model structure, ensuring alignment with other metrics
- **Final calculation**: The final metric value is consistently 0 for all time periods, chains, and products, processed through the `finalize_metric_token_incentives` macro which applies schema validation, ID validation, forward-filling of gaps using the 'fill_zeros' strategy, and chain availability filtering to restrict results to supported blockchain networks

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

Value of native tokens distributed as incentives.

Aperture

Token incentives

Token incentives

Competitive landscape

Chain breakdown