Swappers provide liquidity and execute trades. They receive trading fees charged for each swap.

Mean Finance is a protocol that enables users to Dollar Cost Average (DCA) any ERC20 into any ERC20 with their preferred period frequency.

Mean Finance team owns and governs the protocol. They currently take a cut of the total trading fees paid by traders (revenue).

github

twitter

discord

website

Exchanges (DEX)

Mean Finance

# Mean Finance Trade count Methodology

## 1. Overview

This metric calculates the daily number of unique DCA (Dollar Cost Averaging) trades executed on the Mean Finance protocol. Mean Finance allows users to set up automated, recurring trades that execute over time to average out price volatility. The metric counts distinct transactions that contain completed swap events, providing insight into the platform's trading activity and user engagement across multiple blockchain networks.

## 2. Data sources

- **Mean Finance DCAHub contract events**: Parsed `DCAHub_Swapped` events from Mean Finance v2 smart contracts deployed across five blockchains (Ethereum, Optimism, Polygon, Arbitrum, and BSC)
- **Blockchain transaction data**: Transaction metadata including transaction hashes, block timestamps, and log indices for event ordering
- **Chain availability configuration**: Data availability windows for each supported blockchain to ensure accurate reporting periods

## 3. Step-by-step calculation

### Component A: Raw trade event extraction
- **Purpose**: Extracts all completed DCA swap transactions from Mean Finance contracts across supported chains
- **Logic**: Collects `DCAHub_Swapped` events from Mean Finance v2 contracts on Ethereum, Optimism, Polygon, Arbitrum, and BSC. Each event represents a completed DCA swap execution. The swap information contains an array of token pairs that were processed in the transaction. This array is expanded using cross join operations to create individual records for each token pair swap within a transaction.
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for unique transaction identification, `log_index` for event ordering, contract `address` as the account address, `tokenA` and `tokenB` for the swapped token pair, and `totalAmountToSwapTokenA` and `totalAmountToSwapTokenB` for swap amounts

### Component B: Business classification and standardization
- **Purpose**: Applies consistent business taxonomy and data formatting to all trade records
- **Logic**: Each trade record is classified with standardized business categories. All Mean Finance trades are categorized as 'Exchange AMM' business line, 'exchanges' market sector, and 'dex' business segment. The protocol version is set to 'v2' for all current contracts. Token amounts are safely cast to big numeric types to handle large token values. Chain identifiers are normalized to standard names.
- **Key fields**: `chain` identifier, `business_line`, `market_sector_id`, `business_segment_id`, `product_id` (null for Mean Finance), `version`, `token0_address`, `token1_address`, `token0_amount`, `token1_amount`

### Component C: Daily aggregation and trade counting
- **Purpose**: Groups trades by day and counts unique transactions to avoid double-counting
- **Logic**: Block timestamps are truncated to daily boundaries to group trades by day. The aggregation groups by timestamp, chain, and all business classification fields. Trade counting uses distinct count of transaction hashes, which ensures that transactions containing multiple token pair swaps (expanded from the pairs array) are only counted once per transaction. This prevents inflating trade counts when a single DCA execution processes multiple token pairs.
- **Key fields**: `timestamp` (daily), `timestamp_grain` (set to 'day'), `chain_id`, business classification fields, and `trade_count` (distinct transaction hash count)

### Final aggregation
- **Combining components**: Daily trade counts are processed through the `finalize_metric_trade_count` macro which standardizes the output format, applies the 'fill_zeros' strategy to ensure consistent time series data, and adds metadata fields like data source identifier ('meanfinance')
- **Currency conversion**: No currency conversion is applied as this is a count metric, not a value metric
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with incremental processing that includes a lookback window to capture any late-arriving data
- **Final calculation**: The final trade count represents the number of distinct DCA transactions that executed swaps on each day, per chain, maintaining the business classification dimensions for analytical flexibility. Chain availability filtering is applied to ensure only data from periods with reliable chain data coverage is included in the final results

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

Number of trades executed on a decentralized exchange.

Mean Finance

Trade count

Trade count

Competitive landscape

Chain breakdown