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

Biswap is a non-custodial exchange protocol built on BNB chain. Biswap was founded by an anonymous team and launched in 2021.

BSW tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). Biswap’s investors include Binance Labs.

github

twitter

etherscan

website

Exchanges (DEX)

Biswap

# Biswap Trade count Methodology

## 1. Overview

Trade count measures the number of unique trading transactions executed on the Biswap decentralized exchange (DEX) per day. This metric answers the question "How many distinct trades occurred on Biswap?" and is calculated by counting unique transaction hashes that contain swap events across both Biswap V1 and V3 protocols on the BSC blockchain.

## 2. Data sources

- **Blockchain events**: Parsed BSC `Swap` events from Biswap V1 and V3 smart contracts capturing individual trade executions
- **Factory events**: BSC `PairCreated` events from Biswap V1 factory and `NewPool` events from Biswap V3 factory defining trading pair configurations
- **Function call traces**: BSC transaction traces for Biswap V3 `swapY2X` and `swapX2Y` function calls to determine swap directions
- **Transaction data**: BSC transaction records providing user addresses and transaction metadata
- **External data**: End-of-day token price feeds for USD conversion and token metadata registry containing decimals and symbols
- **Data types**: Smart contract event logs, transaction traces, daily price feeds, and token reference data

## 3. Step-by-step calculation

### Component A: Raw trade event extraction
- **Purpose**: Extract individual swap events from Biswap V1 and V3 contracts
- **Logic**: Query BSC blockchain for `Swap` events from Biswap smart contracts starting from launch date (May 23, 2021). For V1, extract `amount0In`, `amount0Out`, `amount1In`, and `amount1Out` parameters from `Pair_Swap_event` logs. For V3, extract `amountX` and `amountY` from `Pool_Swap_event` return values. Join with transaction records to get user addresses and apply status filtering to include only successful transactions.
- **Key fields**: `transaction_hash`, `log_index`, `block_timestamp`, token amounts, pool addresses, user addresses

### Component B: Swap direction determination (V3 only)
- **Purpose**: Determine the directional flow of tokens in V3 swaps
- **Logic**: Parse BSC transaction traces to identify `swapY2X` and `swapX2Y` function calls. For `swapY2X` calls, assign direction multipliers of -1 for X and +1 for Y. For `swapX2Y` calls, assign +1 for X and -1 for Y. Match these directions to swap events by transaction hash to determine net token flow directions.
- **Key fields**: `directionX`, `directionY`, `transaction_hash`, `trace_address`

### Component C: Trading pair metadata enrichment
- **Purpose**: Add token information and fee structures to trades
- **Logic**: Build trading pair registry from factory events. For V1, extract pair creation events with token addresses and apply fixed fee tiers (0.2% standard, 0.1% for specific stable pools). For V3, extract pool creation events with dynamic fee tiers. Join with token metadata to get decimals and symbols for both tokens in each pair.
- **Key fields**: `token0_address`, `token1_address`, `token0_decimals`, `token1_decimals`, `fee_tier`, `account_name`

### Component D: Token amount calculation and normalization
- **Purpose**: Calculate net token amounts and normalize for decimal precision
- **Logic**: For V1 trades, calculate net token amounts as the difference between in and out amounts for each token. For V3 trades, multiply return value amounts by directional multipliers. Apply absolute value to get trade magnitude. Normalize amounts by dividing by 10 raised to the power of token decimals to convert from raw blockchain units to human-readable amounts.
- **Key fields**: `token0_amount`, `token1_amount` (normalized)

### Component E: USD conversion and price manipulation filtering
- **Purpose**: Convert token amounts to USD and filter manipulated trades
- **Logic**: Join normalized token amounts with end-of-day price feeds for both tokens in each pair. Calculate USD values by multiplying token amounts by their respective USD prices. Apply price manipulation filtering by taking the minimum USD value between the two tokens in each trade, defaulting to zero if price data is unavailable. This filtering helps eliminate trades with artificially inflated prices.
- **Key fields**: `trading_volume` (USD value used for filtering)

### Component F: Daily aggregation with transaction preservation
- **Purpose**: Aggregate trades by day while maintaining transaction-level identifiers
- **Logic**: Truncate timestamps to day boundaries and group trades by date, chain, market sector, business segment, and product dimensions. Preserve unique transaction hashes and log indexes to maintain trade-level granularity needed for counting. Sum USD volumes within each group but retain individual trade identifiers.
- **Key fields**: `timestamp` (daily), `transaction_hash`, `log_index`, dimensional grouping fields

### Final aggregation
- **Combining components**: The processed trading data flows through the intermediate model which combines all trade events with their metadata, price information, and volume calculations
- **Currency conversion**: USD conversion occurs before the final counting step and is used for trade validation rather than the final metric value
- **Time aggregation**: Trades are truncated to daily boundaries, and the final count aggregates all trades within each day
- **Final calculation**: Count distinct transaction hashes grouped by day, chain, market sector (exchanges), business segment (dex), and product dimensions. Apply the finalization macro with zero-filling strategy to populate missing days with zero trade counts. Filter results based on chain availability to ensure data quality.

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

Number of trades executed on a decentralized exchange.

BiswapBSW

Trade count

Trade count

Competitive landscape