AlphaQ trades only its own assets. The operator posts its inventory into on-chain market vaults and prices each quote from external oracles with a dynamic fee that falls in calm markets and is discounted for trades that improve market balance. Its income is the spread embedded in its quotes; the swap instruction carries no separate fee field, and there is no governance token.

AlphaQ is a proprietary automated market maker (prop AMM) on Solana, live since July 2025. It describes itself as a hybrid AMM that combines AMM composability with order-book-level efficiency through oracle-based pricing and dynamic fees. It is in private beta and is accessible only through DEX aggregators, which route swaps to its markets when its quote is best.

AlphaQ is operated by a proprietary trading firm that has not disclosed its team; the project publishes a website and documentation but no social accounts.

website

Exchanges (DEX)

AlphaQ

# AlphaQ Average trading volume (per trade) Methodology

## 1. Overview

Average trading volume (per trade) measures the average USD value of a single swap executed on AlphaQ. This metric is calculated by dividing the total daily trading volume by the daily trade count. Insights are provided into the user profile of the platform, which helps distinguish whether the decentralized exchange is primarily utilized by institutional traders executing large transactions or retail users performing smaller swaps.

## 2. Data sources

- **Blockchain events**: Trade instructions executed by the AlphaQ program, covering Solana
- **External data**: End-of-day price feeds and asset metadata

## 3. Step-by-step calculation

### Component A: Trade extraction and normalization

- **Purpose**: Extract raw trade data and normalize asset amounts
- **Logic**: Trade instructions executed by the AlphaQ program are parsed from Solana DEX trades. For each trade, the pool account, token vault accounts, and token mint accounts are identified. Raw asset amounts are normalized by their respective decimal precisions using asset metadata.
- **Key fields**: `block_timestamp`, `pool_address`, `amount`, `token_address`

### Component B: Daily trade count calculation

- **Purpose**: Calculate the total number of trades executed daily
- **Logic**: The total number of trades is calculated by counting the individual fills executed by the AlphaQ program. Each fill is counted as a single trade, meaning multi-hop aggregator routes that interact with multiple AlphaQ pools are counted as multiple distinct trades. These trades are aggregated daily using UTC boundaries.
- **Key fields**: `block_timestamp`, `transaction_id`

### Component C: Daily trading volume calculation

- **Purpose**: Calculate the total USD value of trades executed daily
- **Logic**: Normalized asset amounts for each trade are converted to USD using end-of-day price feeds. To account for potential pricing discrepancies, the trading volume for each fill is valued at the lesser USD value of its two trade legs. These individual trade volumes are then summed to determine the total daily trading volume.
- **Key fields**: `amount`, `price_usd`

### Component D: Average trading volume calculation

- **Purpose**: Calculate the average USD value per trade
- **Logic**: The total daily trading volume is divided by the daily trade count. If the trade count is zero, the resulting average is handled safely to avoid division-by-zero errors. The final average value is output as the average transaction size in USD for the given day.
- **Key fields**: `trading_volume`, `trade_count`

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

AlphaQ

Average trading volume (per trade)

Average trading volume (per trade)

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