Crypto Funding Rate Arbitrage Backtester & Simulator
Test a cross-exchange perpetual funding strategy against historical settlement rates. Configure the long and short venues, position size, execution costs, and holding period to estimate the funding collected and the resulting net profit or loss.
- Tracked symbols
- 1693
- Exchanges
- 43
- Largest current rate
- -800.00 bps
Live defaults last updated (UTC). Current rates are normalized to an eight-hour basis.
How the funding arbitrage simulation works
The backtester aligns historical funding settlements for both legs, applies the selected position size, and subtracts the configured entry and exit costs. Price-inclusive mode can also model the price movement of supported contracts. Results describe the selected historical period and do not predict future returns.
Funding arbitrage backtester questions
The simulator applies historical cross-exchange funding, position size, fees, and holding period to a consistent perpetual futures strategy model.
What does the funding arbitrage backtester calculate?
It estimates the funding payments earned and paid by opposing perpetual futures positions over a historical window, then applies the configured capital, position size, entry fees, and exit fees.
Is cross-exchange funding arbitrage market neutral?
Matched long and short notional reduces directional exposure, but the trade is not risk-free. Contract prices can diverge, funding can change, one leg can be liquidated, and venue or transfer constraints can prevent rebalancing.
How are different funding intervals handled in a backtest?
Rates are aligned to their actual settlement cadence where settlement data is available. Comparable displays may be normalized, but modeled cash flows should accrue on the venue's real payment schedule.
Why do trading fees matter in funding arbitrage?
The strategy opens and closes two legs, so even a seemingly attractive funding spread can be consumed by four fee events, slippage, and any cost of moving or hedging capital.
Does a profitable historical backtest predict future returns?
No. It describes what the configured rules would have produced from available historical data. Future rates, liquidity, fees, execution, and venue reliability can differ materially.
Live funding defaults snapshot