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

Katana is a non-custodial exchange protocol built on Ronin. Katana was founded by Sky Mavis and launched in 2021.

The Ronin team 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)

Katana (Ronin)

# Katana Average trading volume (per user) Methodology

## 1. Overview

This metric calculates the average daily trading volume per daily active user for the Katana DEX on the Ronin blockchain. It answers the business question: "How much volume does each active trader generate on average per day?" The calculation divides total daily trading volume in USD by the number of unique daily active traders.

## 2. Data sources

- **Swap events**: Parsed `Pair_Swap_event` logs from Katana v1 contracts on Ronin, containing token amount changes for each trade
- **Factory events**: Parsed `Factory_PairCreated_event` logs from Katana v1 on Ronin, defining valid trading pairs with token addresses and fee tiers
- **Transaction data**: Ronin transaction records to identify trader addresses for each swap
- **Token metadata**: Token information including decimals, symbols, and names from the standard tokens registry
- **Manual token configuration**: Hardcoded metadata for Katana-specific tokens not in the standard registry (e.g., Smooth Love Potion)
- **Price feeds**: End-of-day token price feeds in USD for currency conversion

## 3. Step-by-step calculation

### Component A: Trade event processing
- **Purpose**: Extract and standardize raw trade data from Katana swap events
- **Logic**: Parse `Pair_Swap_event` logs from Katana v1 contracts on Ronin. Calculate net token amount changes by subtracting `amount0Out` and `amount1Out` from `amount0In` and `amount1In` respectively. Join with Ronin transaction records to identify the trader address (`from_address`) for each swap. Filter to daily granularity by truncating block timestamps to day boundaries.
- **Key fields**: `transaction_hash`, `log_index`, `user_address`, `token0_amount`, `token1_amount`, `account_address` (pair contract)

### Component B: Trading pair metadata
- **Purpose**: Define valid trading pairs and enrich with token information
- **Logic**: Extract trading pairs from `Factory_PairCreated_event` logs, capturing pair contract addresses, token0/token1 addresses, and fee tiers (3000 basis points = 0.3%). Join with standard token metadata and manual token configuration to get decimal places and symbols for each token in the pair. Create account names by concatenating token symbols.
- **Key fields**: `account_address`, `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `fee_tier`

### Component C: Trading volume calculation
- **Purpose**: Convert token amounts to USD trading volume with decimal correction
- **Logic**: Join trade events with trading pair metadata to get token decimal information. Apply decimal correction by dividing absolute token amounts by 10 raised to the token's decimal places. Join with end-of-day price feeds for both tokens in each pair. Convert corrected token amounts to USD by multiplying by respective token prices. Use the minimum USD value between the two tokens in each swap to prevent price manipulation attacks. Sum trading volumes by day, transaction, and log index to avoid double counting.
- **Key fields**: `trading_volume` (USD value), `timestamp` (daily), `token0_amount`, `token1_amount`

### Component D: Daily active users calculation
- **Purpose**: Count unique traders per day efficiently across multiple dimensions
- **Logic**: Extract distinct trader addresses from processed trade events, truncating to daily boundaries. Use HyperLogLog (HLL) probabilistic data structure for memory-efficient distinct counting. Aggregate users across multiple dimensions including project-level, chain-level, user-type, and product-level. The project-level aggregation (`project_dbt_tag` dimension) represents the total unique daily active users across all Katana trading activity.
- **Key fields**: `user_dau` (distinct count), `dimensions`, `timestamp`

### Final aggregation
- **Combining components**: Join daily trading volume metrics with daily active user metrics on matching timestamps. Use inner join to ensure both volume and user data exist for each day. Take the maximum DAU value (since it should be consistent across the join) and sum trading volume.
- **Currency conversion**: USD conversion occurs in the trading volume component using end-of-day price feeds. The minimum USD value between token pairs prevents manipulation while ensuring realistic volume estimates.
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation. Missing days are filled with zero values through the finalize macro.
- **Final calculation**: Divide total daily trading volume by daily active users using safe division to handle edge cases where DAU might be zero. The result represents average USD trading volume per active trader per day.

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

Average trading volume (per user)

Trading volume divided by daily active users.

Katana (Ronin)

Average trading volume (per user)

Average trading volume (per user)

Competitive landscape