Liquidity providers deposit funds into PancakeSwap and receive trading fees from traders (supply-side fees).

PancakeSwap is a non-custodial exchange protocol built on Binance Smart Chain and other blockchains (originally a fork of Uniswap). PancakeSwap was founded by an anonymous team and launched in 2020.

CAKE tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue).

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PancakeSwap

# PancakeSwap Average trading volume (per user) Methodology

## 1. Overview

Average trading volume (per user) is calculated as the average USD trading volume generated per active user (daily) on PancakeSwap V2 and PancakeSwap V3. The average trading volume generated per active user (daily) is calculated by dividing the total daily trading volume by the number of unique active users (daily). Insight into user engagement intensity and the average economic activity per user on the PancakeSwap platform is provided by this metric. A higher average volume is typically associated with a larger presence of institutional traders or high-value liquidity providers.

## 2. Data sources

- **Blockchain events**: `PairCreated` and `PoolCreated` events from `Factory` contracts, `Swap` events from `Pair` contracts, and `Swap` and `Flash` events from `Pool` contracts, covering Arbitrum, Base, BSC, Ethereum, and 2 other chains
- **External data**: End-of-day asset price feeds and asset metadata including decimal precision and symbols
- **Exclusion lists**: A manually maintained denylist of trading pairs with limited price feed support

## 3. Step-by-step calculation

### Component A: Trading pair identification

- **Purpose**: Define all valid PancakeSwap trading pairs across both V2 and V3 protocols
- **Logic**: Trading pair contract addresses are extracted from factory creation events. For PancakeSwap V2, `PairCreated` events are used to identify the created pair contract address. For PancakeSwap V3, `PoolCreated` events are used to identify pool contract addresses along with fee tier information. These addresses are joined with asset metadata to retrieve decimal precision and symbols for both assets in each pair. Composite pair names are created using asset symbols. Pairs with insufficient price feed coverage are filtered out using a manually maintained denylist.
- **Key fields**: `account_address`, `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `fee_tier`, `account_name`

### Component B: Raw trade extraction

- **Purpose**: Capture all swap transactions from PancakeSwap V2 and V3 protocols
- **Logic**: Swap events are extracted from pair and pool contracts. For PancakeSwap V2 swaps, net asset amounts are calculated by subtracting outbound amounts from inbound amounts for each asset. For PancakeSwap V3 swaps, direct net change values are extracted from the event parameters. Protocol fee information is included for PancakeSwap V3 swaps. These events are joined with transaction records to identify the originating user address from the transaction sender field. Swaps from denylisted trading pairs are filtered out.
- **Key fields**: `transaction_hash`, `user_address`, `account_address`, `token0_amount`, `token1_amount`, `block_timestamp`

### Component C: Flash loan user identification

- **Purpose**: Identify users who performed flash loans to include in active users (daily) counts
- **Logic**: `Flash` events are extracted from PancakeSwap V3 pool contracts. These events are joined with transaction records to identify user addresses. Flash loans from denylisted pools are filtered out. Flash loan users are classified as active users (daily) even if traditional swaps are not performed.
- **Key fields**: `user_address`, `account_address`, `block_timestamp`

### Component D: Volume calculation and USD conversion

- **Purpose**: Convert raw asset amounts to USD trading volume with manipulation protection
- **Logic**: For each trade, asset amounts are normalized by dividing by the appropriate decimal precision from asset metadata. Normalized amounts are joined with end-of-day price feeds to determine USD values for both assets. To protect against wash trading and price manipulation, trades where the USD values of the two legs diverge by more than 100x are flagged as price outliers and excluded. For the remaining trades, anti-manipulation logic is applied by selecting the lesser of the two USD values calculated from the pair's assets. Volume inflation from trades involving assets with inaccurate or manipulated price feeds is prevented by this approach. Trades are aggregated by day to calculate total daily trading volume.
- **Key fields**: `trading_volume`, `timestamp`, `token0_amount`, `token1_amount`

### Component E: Active users (daily) calculation

- **Purpose**: Count unique users who traded or executed flash loans each day
- **Logic**: User addresses from both swap transactions and flash loan transactions are combined. Activity is grouped by calendar day using timestamp truncation. Unique user addresses are aggregated and deduplicated to calculate the daily count of active users (daily).
- **Key fields**: `user_dau`, `timestamp`, `user_address`

### Component F: Final aggregation and average calculation

- **Purpose**: Calculate the average trading volume per active user (daily)
- **Logic**: Daily trading volume is joined with active users (daily) counts on the same timestamp. Total daily trading volume is divided by the active users (daily) count using safe division to handle cases where the user count is zero. The average USD trading volume generated per active user (daily) is calculated as the final output.
- **Key fields**: `trading_volume`, `user_dau`, `trading_volume_avg_per_user`

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

Average trading volume (per user)

Trading volume divided by daily active users.

PancakeSwapCAKE

Average trading volume (per user)

Average trading volume (per user)

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