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

LFJ (previously Trader Joe) is a non-custodial exchange protocol built on Avalanche (originally a fork of SushiSwap). LFJ was founded by an anonymous team and launched in 2021.

JOE tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). LFJ's investors include Three Arrows Capital, DeFiance Capital, GBV Capital, Mechanism Capital, etc.

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# LFJ Trade count Methodology

## 1. Overview

The TraderJoe trade count metric measures the number of unique trading transactions executed daily across all TraderJoe protocol versions and supported blockchain networks. This metric counts distinct transactions that performed token swaps on TraderJoe's automated market maker (AMM) exchanges, providing insight into daily trading activity and user engagement across the platform's ecosystem.

The calculation aggregates swap transactions from four protocol versions (V1, V2, V2.1, V2.2) across five blockchain networks, applies data quality filters, and counts unique transaction hashes on a daily basis.

## 2. Data sources

- **TraderJoe V1 swap events**: Parsed `Pair_Swap_event` logs from TraderJoe V1 pair contracts on BSC and Avalanche networks
- **TraderJoe V2 swap events**: Parsed `LBPair_Swap_event` logs from TraderJoe V2 liquidity book pair contracts on Arbitrum, BSC, and Avalanche
- **TraderJoe V2.1 swap events**: Parsed `LBPairV2_Swap_event` logs from upgraded V2 contracts on Ethereum, Arbitrum, BSC, and Avalanche
- **TraderJoe V2.2 swap events**: Parsed `LBPairV22_Swap_event` logs from the latest V2 contracts on Arbitrum and Avalanche
- **Blockchain transaction records**: Transaction data from Ethereum, Arbitrum, BSC, and Avalanche providing user addresses and timestamps
- **Trading pair metadata**: Token addresses, decimals, and symbols from factory contract pair creation events across all protocol versions
- **Token price feeds**: End-of-day USD price data for tokens traded on TraderJoe
- **Fee parameter events**: Protocol fee configuration data for V2 revenue calculations
- **Denylist configuration**: Hardcoded list of trading pairs excluded due to limited price feed support

## 3. Step-by-step calculation

### Component A: V1 trade extraction
- **Purpose**: Extract and standardize swap events from TraderJoe V1 protocol on BSC and Avalanche
- **Logic**: Query `Pair_Swap_event` logs from V1 pair contracts, joining with blockchain transaction data to get user addresses. Calculate net token amount changes by subtracting `amount0Out` from `amount0In` for token0, and `amount1Out` from `amount1In` for token1. Filter out trades from denylisted trading pairs that have limited price feed support. Apply incremental loading with configurable lookback period for data freshness.
- **Key fields**: `transaction_hash`, `log_index`, `block_timestamp`, `account_address` (trading pair), `user_address`, `token0_amount`, `token1_amount`

### Component B: V2 trade extraction  
- **Purpose**: Extract and standardize swap events from TraderJoe V2 protocol on Arbitrum, BSC, and Avalanche
- **Logic**: Query `LBPair_Swap_event` logs from V2 liquidity book pair contracts, joining with transaction data. Use the `swapForY` boolean field to determine trade direction and appropriately assign `amount_in` and `amount_out` to token0 or token1 based on swap direction. When `trade_direction` is true, token0 receives input amount and token1 provides output; when false, the opposite occurs. Fee amounts are similarly assigned based on trade direction.
- **Key fields**: `transaction_hash`, `log_index`, `trade_direction`, `amount_in`, `amount_out`, `fees`, calculated `token0_amount`, `token1_amount`

### Component C: V2.1 trade extraction
- **Purpose**: Extract swap events from upgraded V2 contracts with packed amount encoding
- **Logic**: Query `LBPairV2_Swap_event` logs from V2.1 contracts on Ethereum, Arbitrum, BSC, and Avalanche. Use JavaScript decoding function to unpack encoded amount parameters (`amountsIn`, `amountsOut`, `protocolFees`, `totalFees`) which contain both token amounts packed into single hex values. The decoding extracts lower 128 bits for tokenX amounts and upper 128 bits for tokenY amounts. Calculate net token changes by subtracting out amounts from in amounts for each token.
- **Key fields**: Encoded `amountsIn`, `amountsOut`, `protocolFees`, `totalFees` parameters decoded to separate `token0_amount`, `token1_amount`, `token0_fees`, `token1_fees`, `token0_revenue`, `token1_revenue`

### Component D: V2.2 trade extraction
- **Purpose**: Extract swap events from latest V2 contracts with same encoding as V2.1
- **Logic**: Query `LBPairV22_Swap_event` logs from V2.2 contracts on Arbitrum and Avalanche using identical JavaScript decoding logic as V2.1. Handle the same packed amount parameters to extract individual token amounts, fees, and revenue shares for both tokens in each trading pair.
- **Key fields**: Same encoded parameters as V2.1, decoded to `token0_amount`, `token1_amount`, `token0_fees`, `token1_fees`, `token0_revenue`, `token1_revenue`

### Component E: Trading pair metadata enrichment
- **Purpose**: Add token metadata and filter invalid pairs
- **Logic**: Join all trades with trading pair dimension data sourced from factory contract pair creation events. Retrieve token addresses, decimal places, and symbols for both tokens in each pair. Filter out trading pairs included in the denylist configuration due to limited price feed support for low-liquidity tokens. This ensures only pairs with reliable pricing data contribute to the final metric.
- **Key fields**: `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `account_name` (token pair symbol)

### Component F: Daily aggregation and decimal correction
- **Purpose**: Aggregate trades by day and standardize token amounts
- **Logic**: Group all trades by daily timestamps, transaction hash, log index, chain, and business dimensions. Correct token amounts by dividing raw values by 10 raised to the respective token's decimal places to get human-readable amounts. Sum absolute values of token amounts, fees, and revenue across all trades within each group to handle both positive and negative amount changes from different trade directions.
- **Key fields**: `timestamp` (daily), `token0_amount`, `token1_amount` (decimal-corrected), `token0_fees`, `token1_fees`, `token0_revenue`, `token1_revenue`

### Component G: USD conversion and price manipulation filtering
- **Purpose**: Convert token amounts to USD values with anti-manipulation controls
- **Logic**: Join aggregated daily trades with end-of-day token price feeds for both tokens in each pair. Calculate USD values by multiplying token amounts with respective USD prices. Apply price manipulation filter by taking the minimum USD value between the two token amounts in each trade, which prevents inflated volumes from price discrepancies or manipulation attempts. Sum fee and revenue USD values across both tokens without the minimum filter.
- **Key fields**: `trading_volume` (minimum of token0 and token1 USD values), `fees` (sum of both token USD values), `revenue` (sum of both token USD values)

### Final aggregation
- **Combining components**: All trade data flows through the intermediate trading volumes model which combines V1, V2, V2.1, and V2.2 trades with standardized fields and USD conversions
- **Currency conversion**: End-of-day token prices convert all amounts to USD values with price manipulation protection via minimum value selection
- **Time aggregation**: All trades are aggregated to daily boundaries using `timestamp_trunc` function on block timestamps  
- **Final calculation**: Count distinct `transaction_hash` values grouped by timestamp, chain, market sector, business segment, and product dimensions. Apply the `finalize_metric_trade_count` macro with fill_zeros strategy to ensure consistent daily data points and handle missing dates. Filter results based on chain availability configuration to include only supported blockchain networks.

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

Number of trades executed on a decentralized exchange.

LFJJOE

Trade count

Trade count

Competitive landscape

Chain breakdown