Liquidity providers deposit funds into Ramses and stake their LP tokens to receive RAM tokens in proportion to their share of the votes (token incentives).

Ramses is a non-custodial exchange protocol built on Arbitrum. Ramses was founded by pseudonyms Dog and North in 2023.

RAM tokenholders own and govern the protocol. They vote which pools they wish to earn trading fees from (revenue).

github

twitter

discord

etherscan

website

Exchanges (DEX)

Ramses Exchange

# Ramses Exchange Trading volume Methodology

## 1. Overview

Ramses trading volume measures the total USD value of tokens traded across the Ramses decentralized exchange on Arbitrum. This includes both v1 (Legacy Pairs) and v2 (Concentrated Liquidity Pools) trading activity. The metric aggregates daily trading volumes by taking the lower USD value between the two tokens in each swap to prevent price manipulation from affecting the calculation.

## 2. Data sources

The calculation relies on several key data sources:

- **Arbitrum blockchain events**: Parsed `Swap` events from Ramses v1 `LegacyPair` contracts and Ramses v2 `Pool` contracts, capturing token amounts and swap details
- **Factory creation events**: `PairCreated` events from Ramses v1 Factory and `PoolCreated` events from Ramses v2 Factory contracts to identify valid trading pairs
- **Transaction records**: Arbitrum transaction data to link contract interactions to user addresses
- **End-of-day price feeds**: Token price data for USD conversion of trading volumes
- **CoinGecko price data**: Special price feed for the RAM token (address `0xaaa6c1e32c55a7bfa8066a6fae9b42650f262418`) sourced from CoinGecko API
- **Token metadata**: Token symbols and decimal precision information for proper amount calculations

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extract and standardize swap events from both Ramses v1 and v2 contracts
- **Logic**: The system collects `Swap` events from Ramses v1 `LegacyPair` contracts and v2 `Pool` contracts on Arbitrum since the launch date of March 14, 2023. For v1 swaps, token amounts are calculated as the net change by subtracting `amount_out` from `amount_in` for each token. For v2 swaps, the system uses the direct `amount0` and `amount1` values. Each swap record includes the transaction hash, log index, contract address, user addresses, and raw token amounts for both tokens in the pair.
- **Key fields**: `transaction_hash`, `log_index`, `account_address` (contract address), `user_address`, `token0_amount`, `token1_amount`, `product_id` (legacypair or concentratedliquiditypool)

### Component B: Trading pair metadata
- **Purpose**: Create a registry of valid trading pairs with their token composition and metadata
- **Logic**: The system processes `PairCreated` events from Ramses v1 Factory and `PoolCreated` events from v2 Factory to identify all valid trading pair contracts. Each pair record includes the contract address, the two underlying token addresses, and version information. This data is enriched with token metadata including decimal precision and symbols to create human-readable pair names in the format "TOKEN0-TOKEN1".
- **Key fields**: `account_address`, `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `account_name`, `version`

### Component C: Volume calculation with decimal correction
- **Purpose**: Join trade events with pair metadata and convert raw token amounts to human-readable values
- **Logic**: Trade events are joined with trading pair data using the contract address to obtain token addresses and decimal information. Raw token amounts are converted to human-readable values by dividing by 10 raised to the power of each token's decimal precision. The absolute value is taken to ensure positive amounts regardless of swap direction. Timestamps are truncated to day boundaries for daily aggregation.
- **Key fields**: `timestamp` (daily), `chain`, `product_id`, `token0_address`, `token1_address`, `token0_amount`, `token1_amount`

### Component D: Price data preparation
- **Purpose**: Create a comprehensive price dataset combining standard feeds with custom RAM token pricing
- **Logic**: The system combines end-of-day token prices from standard price feeds with special CoinGecko pricing for the RAM token. The RAM token requires separate handling because it's not available in standard price feeds. All other tokens on Arbitrum use the standard price feed data. This creates a unified price dataset covering all tokens traded on Ramses.
- **Key fields**: `timestamp`, `chain`, `token_address`, `price_usd`

### Component E: USD conversion and price manipulation protection
- **Purpose**: Convert token amounts to USD values while filtering out potential price manipulation
- **Logic**: For each trade, the system calculates USD values for both tokens by multiplying the token amounts by their respective prices. To prevent price manipulation from inflating volumes, the calculation uses the lesser of the two USD values (`least()` function). This means if one token has an artificially inflated price, the volume will be based on the more reliable token's value. Trades without price data for either token are excluded from the calculation.
- **Key fields**: `trading_volume` (USD value using minimum of token0_value and token1_value)

### Final aggregation
- **Combining components**: Daily trading volumes are summed by chain, product type (Legacy Pair vs Concentrated Liquidity Pool), and version
- **Currency conversion**: USD conversion uses end-of-day token prices, with special CoinGecko pricing for the RAM token
- **Time aggregation**: Volumes are aggregated on daily boundaries using timestamp truncation
- **Final calculation**: The final metric represents the sum of all daily trading volumes across Ramses v1 and v2, with price manipulation protection applied through the minimum USD value approach

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

Total value of spot trades executed on the exchange.

Ramses ExchangeRAM

Trading volume

Trading volume

Competitive landscape

Chain breakdown