# Meteora Liquidity Pools Trading volume Methodology

## 1. Overview

The total value of trades executed on Meteora Liquidity Pools is measured by trading volume. Trading activity and liquidity utilization within the dynamic automated market maker (AMM) and dynamic liquidity market maker (DLMM) pools of the protocol are represented by this metric, with pools associated with Meteora Launchpad being excluded. The capacity of the protocol to generate trading fees and revenue for liquidity providers is indicated by this metric.

## 2. Data sources

- **Blockchain events**: `Migration` instructions from the `DBC` program (`dbcij3LWUppWqq96dh6gJWwBifmcGfLSB5D4DuSMaqN`), trade instructions from the Meteora DLMM (`LBUZKhRxPF3XUpBCjp4YzTKgLccjZhTSDM9YuVaPwxo`), Meteora AMM V1 (`Eo7WjKq67rjJQSZxS6z3YkapzY3eMj6Xy8X5EQVn5UaB`), and Meteora AMM V2 (`cpamdpZCGKUy5JxQXB4dcpGPiikHawvSWAd6mEn1sGG`) programs, and asset balance changes, covering Solana
- **External data**: End-of-day price feeds for traded assets, and asset metadata for decimal normalization

## 3. Step-by-step calculation

### Component A: Meteora Liquidity Pools trade extraction and normalization

- **Purpose**: Extract and normalize raw trade data from the relevant Solana programs
- **Logic**: Trade instructions are filtered from the Solana decentralized exchange trade records where the executing account or outer executing account matches the Meteora DLMM (`LBUZKhRxPF3XUpBCjp4YzTKgLccjZhTSDM9YuVaPwxo`), Meteora AMM V1 (`Eo7WjKq67rjJQSZxS6z3YkapzY3eMj6Xy8X5EQVn5UaB`), Meteora AMM V2 (`cpamdpZCGKUy5JxQXB4dcpGPiikHawvSWAd6mEn1sGG`), or DBC (`dbcij3LWUppWqq96dh6gJWwBifmcGfLSB5D4DuSMaqN`) program accounts. Raw asset amounts are extracted from these instructions. These amounts are then normalized by decimal precision using asset metadata.
- **Key fields**: `block_timestamp`, `pool_address`, `token_0_address`, `token_1_address`, `amount_0`, `amount_1`

### Component B: Meteora Liquidity Pools product attribution

- **Purpose**: Isolate trades belonging specifically to Meteora Liquidity Pools by filtering out graduated launchpad pools
- **Logic**: Pool accounts that originated from a bonding-curve graduation are identified using `Migration` instructions from the `DBC` program. Trades executed on the Meteora DLMM program are attributed to Meteora Liquidity Pools. Trades executed on the DBC program are attributed to Meteora Launchpad. Trades executed on the Meteora AMM V1 or V2 programs are attributed to Meteora Launchpad if the pool account matches a graduated pool; otherwise, they are attributed to Meteora Liquidity Pools.
- **Key fields**: `pool_address`, `product_id`

### Component C: Wash trading filter

- **Purpose**: Identify and exclude inorganic wash trading volume from Meteora AMM V2 pools
- **Logic**: Daily trading volume and daily reserves are calculated in native units for both asset legs of Meteora AMM V2 pools. Daily turnover ratios are calculated by dividing the daily volume by the daily reserve for each leg. Pool-days where the turnover ratio on both legs exceeds 20 are flagged as inorganic wash trading and are excluded from the trade dataset. This filter is applied only to Meteora AMM V2 pools, as individual vaults are maintained for each pool, allowing reserves to represent the pool's own liquidity depth.
- **Key fields**: `pool_address`, `timestamp`, `turnover_0`, `turnover_1`

### Component D: USD valuation and price-manipulation guard

- **Purpose**: Calculate the USD value of each trade using a conservative one-sided notional method to prevent price manipulation
- **Logic**: Aggregated daily asset amounts are multiplied by their respective end-of-day USD prices. The USD trading volume for each pool-day is calculated by taking the lesser of the two USD-valued legs (asset 0 value and asset 1 value). This conservative one-sided notional calculation is applied to prevent artificial volume inflation from price manipulation of a single asset.
- **Key fields**: `amount_0`, `amount_1`, `price_usd`

### Component E: Daily aggregation and zero-filling

- **Purpose**: Aggregate trading volume to a daily grain and ensure continuous data coverage
- **Logic**: The USD trading volumes are summed by day, chain, and product ID. The aggregated daily values are processed to ensure correct schema casting and data types. Missing days in the time series are filled with zeros to maintain a continuous daily record. Finally, chain availability filters are applied to align the data with active chain configurations.
- **Key fields**: `timestamp`, `trading_volume`

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

Total value of spot trades executed on the exchange.

Trading volume