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 user) Methodology

## 1. Overview

Average trading volume (per user) is defined as the average trading volume generated per unique user over a fixed 24-hour window for AlphaQ. This metric is calculated as total daily trading volume divided by active users (daily), and is used to reflect whether the decentralized exchange is utilized by institutional or retail traders. Because AlphaQ is operated as a proprietary market maker where trades are executed against the operator's own inventory, this metric is used to represent the average size of trades filled directly by the program.

## 2. Data sources

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

## 3. Step-by-step calculation

### Component A: Trade instruction parsing and normalization

- **Purpose**: To parse trade instructions from the AlphaQ program and extract transaction details
- **Logic**: Trade instructions executed by the AlphaQ program are filtered from Solana decentralized exchange trade records. For each trade, the transaction signer, pool account, base and quote mint accounts, and raw asset amounts are extracted. Asset amounts are normalized by decimal precision using asset metadata.
- **Key fields**: `block_timestamp`, `signer`, `pool_address`, `amount_0`, `amount_1`, `token_address_0`, `token_address_1`

### Component B: Daily active user aggregation

- **Purpose**: To calculate the number of active users (daily) interacting with the program
- **Logic**: Transaction signers are identified as the end traders since AlphaQ is accessed via decentralized exchange aggregators. Unique transaction signers are aggregated daily to determine the active users (daily) metric.
- **Key fields**: `block_timestamp`, `signer`

### Component C: Trading volume calculation and USD conversion

- **Purpose**: To calculate the daily trading volume in USD
- **Logic**: Daily trading volume is calculated for each pool account. Because proprietary inventory is traded at oracle-derived quotes without traditional liquidity providers, each swap is valued at the lesser USD value of its two legs. Normalized asset amounts are multiplied by end-of-day price feeds to determine the USD value of each leg, and the lower value is selected and aggregated daily.
- **Key fields**: `amount_0`, `amount_1`, `price_usd`

### Component D: Average trading volume (per user) calculation

- **Purpose**: To calculate the average trading volume generated per user
- **Logic**: The total daily trading volume is divided by the active users (daily) for each day. If no activity is recorded, the metric is filled with zeros.
- **Key fields**: `trading_volume`, `user_dau`

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

Average trading volume (per user)

Trading volume divided by daily active users.

AlphaQ

Average trading volume (per user)

Average trading volume (per user)

Competitive landscape