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 Tradeable assets Methodology

## 1. Overview

The tradeable assets metric measures the cumulative number of unique tokens available for trading on TraderJoe exchanges. This metric answers the question "How many different tokens can users trade on TraderJoe?" and tracks the growth of token diversity over time. The calculation identifies every token that has ever been part of a trading pair and maintains a running total as new tokens are added through pair creation events.

## 2. Data sources

The calculation relies on the following data sources:
- **Pair creation events**: Parsed `PairFactory_PairCreated` events from TraderJoe V1 deployments on Avalanche and BSC blockchains
- **Liquidity book events**: Parsed `LBFactory_LBPairCreated`, `LBFactoryV2_LBPairCreated`, and `LBFactoryV22_LBPairCreated` events from TraderJoe V2 deployments across Ethereum, Arbitrum, BSC, and Avalanche blockchains
- **Token metadata**: Token symbol and decimal information for display purposes
- **Blockchain event logs**: Transaction timestamps and block information from supported chains

## 3. Step-by-step calculation

### Component A: Trading pair identification
- **Purpose**: Collect all trading pairs created across TraderJoe versions and chains
- **Logic**: Query pair creation events from multiple TraderJoe factory contracts across different versions and blockchains. V1 uses `PairFactory_PairCreated_event` while V2 uses various `LBFactory*_LBPairCreated_event` schemas. Each event contains the addresses of two tokens (`token0` and `token1`) that form the trading pair, along with the pair contract address and creation timestamp. The process extracts these token addresses, pair addresses, chain information, and block timestamps from all supported TraderJoe deployments.
- **Key fields**: `token0_address`, `token1_address`, `account_address` (pair contract), `block_timestamp`, `chain`, `version`

### Component B: Token address extraction
- **Purpose**: Create a comprehensive list of all unique tokens from trading pairs
- **Logic**: From each trading pair record, extract both token addresses separately to ensure every token that can be traded is captured. This involves taking each pair's `token0_address` and `token1_address` and treating them as individual tradeable assets. The process creates separate records for each token address along with its first appearance timestamp and chain, ensuring no tradeable token is missed regardless of its position in the pair.
- **Key fields**: `timestamp`, `chain`, `token_address`

### Component C: First appearance tracking  
- **Purpose**: Identify when each token first became tradeable
- **Logic**: For each unique combination of token address and chain, find the earliest timestamp when that token appeared in any trading pair creation event. This determines the date when each token first became available for trading on TraderJoe. The process groups by token address and chain, then applies a minimum aggregation on the timestamp to find the first occurrence.
- **Key fields**: `timestamp` (minimum), `chain`, `token_address`

### Component D: Daily new asset counting
- **Purpose**: Count how many new tokens became tradeable each day
- **Logic**: Group the first appearance data by day and chain, then count the distinct number of tokens that had their first appearance on each specific date. This creates a daily time series showing how many new tradeable assets were added to the platform each day. Days with no new tokens are initially excluded from this step.
- **Key fields**: `timestamp` (daily), `chain`, `asset_count`

### Component E: Gap filling
- **Purpose**: Ensure continuous daily time series with zero values for inactive days
- **Logic**: Use the fill_zeros macro to create records for any missing days between the first and last appearance dates, setting the asset count to zero for days when no new tokens were added. This ensures a complete daily time series without gaps, which is essential for accurate cumulative calculations.
- **Key fields**: `timestamp`, `chain`, `asset_count` (filled with zeros)

### Final aggregation
- **Combining components**: The gap-filled daily new asset counts serve as the input for the final cumulative calculation
- **Currency conversion**: Not applicable - this metric counts tokens rather than monetary values
- **Time aggregation**: Daily granularity with cumulative calculation using window functions
- **Final calculation**: Apply a running sum window function partitioned by chain and ordered by timestamp to convert daily new token counts into cumulative tradeable asset totals. The formula calculates `SUM(daily_new_assets) OVER (PARTITION BY chain ORDER BY timestamp)` to maintain separate cumulative counts for each blockchain while preserving chronological order.

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

Number of unique tokens tradeable on the exchange.

LFJJOE

Tradeable assets

Tradeable assets

Competitive landscape

Chain breakdown