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Meteora

# Meteora Average trading volume (per trade) Methodology

## 1. Overview

Average trading volume (per trade) is calculated as the average value of a single trade across Meteora products, including Meteora Launchpad and Meteora Liquidity Pools. This metric is calculated by dividing the total daily trading volume by the daily trade count. It is used as an indicator of the user base composition, where higher average values are typically associated with institutional activity and lower values are associated with retail-oriented usage.

## 2. Data sources

- **Blockchain events**: Swap instructions from the Meteora Launchpad and Meteora Liquidity Pools programs, and asset balance changes from Solana accounts, covering Solana
- **External data**: End-of-day price feeds for traded assets

## 3. Step-by-step calculation

### Component A: Trade extraction and product categorization

- **Purpose**: Identify and normalize swap activity across different Meteora programs
- **Logic**: Swap instructions are parsed from Solana DEX trades. Trades are filtered based on the executing program account and categorized into Meteora Launchpad or Meteora Liquidity Pools, with trades from the DLMM program categorized under Meteora Liquidity Pools. DAMM pools originating from a Dynamic Bonding Curve (DBC) graduation are identified using `DBC_Migration` and attributed to Meteora Launchpad. Base and quote asset amounts are extracted for each trade and normalized by decimal precision. To filter out wash trading activity, daily trading volumes for both legs of DAMM V2 pools are compared against their respective reserves. Pool-days where the daily volume on both legs exceeds 20 times the reserve are flagged as inorganic and excluded from the final dataset.
- **Key fields**: `amount_0`, `amount_1`, `token_0_address`, `token_1_address`, `pool_address`, `product_id`

### Component B: Trading volume calculation

- **Purpose**: Determine the USD value of trading activity using a conservative valuation method
- **Logic**: Both legs of every trade (base and quote) are converted to USD using end-of-day price feeds. A conservative one-sided notional convention is applied, where the trading volume for a single swap is defined as the lesser of the two USD-valued legs. These values are then summed to determine the total daily trading volume.
- **Key fields**: `amount_0`, `amount_1`, `price_usd`

### Component C: Trade count aggregation

- **Purpose**: Calculate the total number of individual swap events
- **Logic**: The total number of unique swap instructions is aggregated on a daily basis. Each parsed instruction from the Meteora programs is treated as a single trade. Aggregator transactions containing multiple Meteora swaps are decomposed so that each individual swap is included in the total count.

### Component D: Average value derivation

- **Purpose**: Calculate the final average trade size
- **Logic**: The total daily trading volume (calculated in Component B) is divided by the daily trade count (calculated in Component C). The average USD volume per trade is derived from this resulting value. This calculation is performed at the project level, aggregating data across all identified Meteora programs.
- **Key fields**: `trading_volume`, `trade_count`

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

MeteoraMET

Average trading volume (per trade)

Average trading volume (per trade)

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