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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Exchanges (DEX)

PancakeSwap

# PancakeSwap Trade count Methodology

## 1. Overview

PancakeSwap trade count measures the total number of unique trading transactions executed on the PancakeSwap decentralized exchange per day. This metric tracks user trading activity by counting distinct transaction hashes that contain swap events, providing insight into trading frequency and platform usage across PancakeSwap V2 and V3 deployments on multiple chains.

## 2. Data sources

- **Blockchain events**: Parsed `Swap` events from PancakeSwap V2 pairs and V3 pools, `PairCreated` (V2) and `PoolCreated` (V3) events from PancakeSwap Factory contracts, and blockchain transaction records, covering Ethereum, BSC, Arbitrum, Base, and 2 other chains
- **External data**: End-of-day token price feeds for USD conversion and token metadata including decimals and symbols
- **Configuration data**: Hardcoded denylist of 5 specific trading pair addresses with limited price feed support

## 3. Step-by-step calculation

### Component A: Raw swap event extraction

- **Purpose**: Collect all swap events from PancakeSwap V2 and V3 contracts across supported chains
- **Logic**: Extract `Swap` events from V2 pair contracts and V3 pool contracts. For V2, calculate token amounts as the difference between `amountIn` and `amountOut` values. For V3, use direct `amount0` and `amount1` values. Include protocol fees for V3 trades. Filter out events from denylisted trading pair addresses (5 hardcoded pairs with liquidity issues). Join with blockchain transaction data to obtain user addresses from the `from_address` field
- **Key fields**: `transaction_hash`, `log_index`, `block_timestamp`, swap amounts, `sender` address, contract `address`

### Component B: Trading pair validation and metadata enrichment

- **Purpose**: Validate that swap events come from legitimate PancakeSwap pairs and enrich with token metadata
- **Logic**: Join swap events with trading pairs identified from Factory contract events. Only include pairs created through official PancakeSwap Factory contracts via `PairCreated` events (V2) or `PoolCreated` events (V3). Enrich with token metadata including decimal places, symbols, and fee tiers. Apply additional filtering to exclude the 5 denylisted trading pairs due to limited price feed support
- **Key fields**: `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `fee_tier`, pair `account_name`

### Component C: Token amount normalization and USD conversion

- **Purpose**: Standardize token amounts and convert to USD values for filtering
- **Logic**: Normalize token amounts by dividing by 10 raised to the power of each token's decimal places. Join with end-of-day price feeds to get USD prices for both tokens in each trading pair. Convert token amounts to USD values. To filter out price manipulation, take the lesser of the two USD amounts (token0 USD value vs token1 USD value) as the final trading volume. Aggregate amounts daily while maintaining transaction-level granularity via `transaction_hash` and `log_index`
- **Key fields**: Normalized `token0_amount` and `token1_amount`, USD `trading_volume`, `price_usd` from price feeds

### Component D: Daily aggregation and trade counting
- **Purpose**: Group trades by day and count unique transactions
- **Logic**: Truncate timestamps to daily boundaries and group by date, chain, market sector, business segment, and product. Count distinct `transaction_hash` values to get the number of unique trading transactions per day. Each unique transaction hash represents one trade, regardless of how many swap events it contains
- **Key fields**: Daily `timestamp`, `chain_id`, distinct `transaction_hash` count as `trade_count`

### Final aggregation

- **Combining components**: The processed trade data flows through all components sequentially, maintaining transaction-level detail until the final counting step
- **Currency conversion**: USD conversion uses end-of-day price feeds with manipulation filtering via the "least" function
- **Time aggregation**: Daily boundaries are created by truncating timestamps to day level, with trades grouped by date
- **Final calculation**: Count distinct transaction hashes per day to get the total number of unique trading transactions, applying zero-filling for days with no trading activity

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

Number of trades executed on a decentralized exchange.

PancakeSwapCAKE

Trade count

Trade count

Competitive landscape

Chain breakdown