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

ApeSwap is a non-custodial exchange protocol built originally on BNB Chain. ApeSwap was founded by an anonymous team and launched in 2021.

BANANA 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)

ApeSwap

# ApeSwap Average trading volume (per trade) Methodology

## 1. Overview

Trading volume average per trade count measures the average USD value per trade executed on the ApeSwap decentralized exchange. This metric is calculated by dividing the total daily trading volume (in USD) by the total number of trades for the same period. It provides insight into the typical trade size on the platform and helps assess user trading behavior and market depth.

## 2. Data sources

- **ApeSwap swap events**: Parsed `Swap` events from ApeSwap's `ApePair` contracts across Ethereum, Polygon, Arbitrum, and BSC networks containing token amount changes
- **ApeSwap factory events**: Parsed `PairCreated` events from ApeSwap's `ApeFactory` contracts identifying trading pair addresses, token pairs, and fee structures
- **Blockchain transaction data**: Transaction records from Ethereum, Polygon, Arbitrum, and BSC providing user addresses and transaction metadata
- **Token metadata**: Token information including decimal precision and symbols for proper amount calculations
- **End-of-day price feeds**: Daily token price data in USD for currency conversion

## 3. Step-by-step calculation

### Component A: Trade extraction and processing
- **Purpose**: Extract and process individual swap transactions from ApeSwap contracts
- **Logic**: Parse `Swap` events from `ApePair` contracts across supported chains. For each swap, calculate the net change in token amounts by subtracting outbound amounts (`amount0Out`, `amount1Out`) from inbound amounts (`amount0In`, `amount1In`) for both tokens in the pair. Join with transaction data to identify the actual user address and filter trades from February 10, 2021 onwards.
- **Key fields**: `amount0In`, `amount0Out`, `amount1In`, `amount1Out` for token amounts, `sender` for contract user, transaction `from_address` for actual user

### Component B: Trading pair identification
- **Purpose**: Map swap events to their corresponding trading pairs and token information
- **Logic**: Use `PairCreated` events from `ApeFactory` contracts to identify valid trading pairs with their token addresses. Apply a standard 0.2% fee tier (2000 basis points divided by 1,000,000) across all pairs. Join with token metadata to obtain decimal precision and symbols for each token in the pair.
- **Key fields**: `pair` address from factory events, `token0` and `token1` addresses, token `decimals` and `symbol` from metadata

### Component C: Volume calculation with price manipulation protection
- **Purpose**: Convert token amounts to USD values and apply anti-manipulation filtering
- **Logic**: Join processed trades with trading pair data and correct token amounts by dividing by 10 raised to the token's decimal precision. Convert both token amounts to USD using end-of-day price feeds. To prevent price manipulation from affecting volume calculations, take the minimum USD value between the two tokens in each swap rather than using both sides of the trade.
- **Key fields**: Corrected `token0_amount` and `token1_amount`, USD `price_usd` from price feeds, calculated `trading_volume` as minimum USD value

### Component D: Daily trade counting
- **Purpose**: Count the number of unique trades per day
- **Logic**: Group processed trades by day and count distinct transaction hashes to determine the total number of trades. This approach ensures that multi-step transactions or complex swaps are counted as single trades while avoiding double-counting.
- **Key fields**: Daily `timestamp`, distinct `transaction_hash` for trade counting

### Final aggregation
- **Combining components**: Join daily trading volume totals with daily trade counts on the same timestamp
- **Currency conversion**: All amounts converted to USD using end-of-day price feeds with price manipulation protection applied
- **Time aggregation**: Data aggregated to daily boundaries using timestamp truncation
- **Final calculation**: Divide total daily trading volume by total daily trade count using safe division to handle days with zero trades, resulting in the average USD value per trade

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

ApeSwapABOND

Average trading volume (per trade)

Average trading volume (per trade)

Competitive landscape