Liquidity providers deposit funds into DFX and receive a share of trading fees (supply-side fees).

DFX is a decentralized foreign exchange protocol deployed on Polygon, Ethereum & Arbitrum. DFX was founded in 2021 by Kevin Zhang and Adrian Li.

DFX 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)

DFX Finance

# DFX Finance Trade count Methodology

## 1. Overview

The DFX trade count metric measures the daily number of unique trades executed on the DFX protocol across Ethereum, Polygon, and Arbitrum networks. This metric counts distinct transactions containing trade events rather than individual swap operations, providing insight into daily trading activity and user engagement. The calculation aggregates `Trade` events from multiple DFX contract versions and counts unique transaction hashes per day.

## 2. Data sources

The trade count calculation relies on several key data sources:

- **DFX protocol events**: Parsed `Trade` events from DFX protocol contracts across multiple versions (v1 and v2) and chains (Ethereum, Polygon, Arbitrum), including `Curve_Trade_event`, `CurveV2_Trade_event`, and `CurveV22_Trade_event`
- **Transaction data**: Ethereum, Polygon, and Arbitrum transaction records containing timestamps, transaction hashes, and user addresses
- **Contract creation events**: DFX `CurveFactory` contract creation events (`NewCurve_event`) and corresponding function calls (`newCurve_function`) used to establish fee tier information
- **Token metadata**: Token symbols, decimal places, and identifiers for proper amount normalization and display names
- **End-of-day price feeds**: Token price data used in intermediate volume calculations that support the trade count metric

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extract and standardize trade events from multiple DFX protocol contract versions across different blockchains
- **Logic**: The system queries `Trade` events from various DFX contract schemas including v1 `Curve_Trade_event` on Ethereum and Polygon, and v2 `CurveV2_Trade_event` and `CurveV22_Trade_event` on Ethereum, Polygon, and Arbitrum. Each trade event is joined with its corresponding transaction record to obtain user addresses and precise timestamps. The system extracts key trade details including origin and target token addresses, trade amounts, and the pool contract address where the trade occurred.
- **Key fields**: `block_timestamp` for trade timing, `transaction_hash` for unique trade identification, `log_index` for event ordering, `address` for the trading pool contract, `origin` and `target` for the tokens being swapped, `originAmount` and `targetAmount` for trade sizes

### Component B: Fee tier determination
- **Purpose**: Establish fee tier information for each trading pool to support volume calculations
- **Logic**: Fee tiers are determined through two methods. For Arbitrum pools, manually configured fee tiers are applied using hardcoded pool addresses and their corresponding fee percentages. For Ethereum and Polygon pools, fee tiers are extracted from DFX `CurveFactory` contract creation events, specifically from the `epsilon` parameter in the `newCurve` function calls, which is converted from wei to decimal format by dividing by 10^18.
- **Key fields**: `account_address` for the pool contract, `fee_tier` as the calculated fee percentage, `chain` for network identification

### Component C: Trade aggregation and normalization
- **Purpose**: Normalize trade amounts using token decimals and aggregate trades by day while maintaining unique transaction identification
- **Logic**: Trade events are aggregated to daily boundaries using timestamp truncation. Token amounts are normalized by dividing by 10 raised to the power of each token's decimal places. Trades are grouped by day, transaction hash, log index, chain, and business classification fields. The system creates trading pair names by concatenating token symbols. Fee tiers are applied based on a protocol fee start date of February 13, 2023, using an initial fee tier of 0.0005 for earlier trades and contract-specific fee tiers for later trades.
- **Key fields**: `timestamp` truncated to day boundaries, `transaction_hash` for unique trade identification, `token0_amount` and `token1_amount` normalized for decimal places, `account_name` combining token symbols

### Component D: Trade count calculation
- **Purpose**: Count the number of distinct trades per day across different dimensions
- **Logic**: The system counts distinct transaction hashes rather than individual log entries to ensure that multi-step or complex trades within a single transaction are counted only once. Trades are grouped by day, chain, market sector (exchanges), business segment (dex), and product ID. The count function specifically targets the `transaction_hash` field to capture unique trading transactions.
- **Key fields**: `trade_count` as the count of distinct `transaction_hash` values per day and dimension grouping

### Final aggregation
- **Combining components**: All trade data flows through the intermediate trading volumes model before reaching the final trade count calculation, ensuring consistent business logic and dimensional attributes
- **Currency conversion**: While USD conversion occurs in the intermediate volume calculations for consistency, the trade count metric itself focuses purely on transaction counting
- **Time aggregation**: Daily boundaries are established using timestamp truncation to day level, with all trades occurring within a 24-hour period counted toward that day's total
- **Final calculation**: The final metric represents the count of distinct transaction hashes containing DFX trade events per day, grouped by chain and business dimensions, with zero-filling applied to ensure complete time series data and chain availability filtering to match data coverage periods

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

Number of trades executed on a decentralized exchange.

DFX FinanceDFX

Trade count

Trade count

Competitive landscape

Chain breakdown