Automating Perpetual Funding Rate Arbitrage with Stability and Cost Filters
Summary
This document describes a workflow for finding and trading funding rate spreads across centralized and decentralized perpetual exchanges. It collects cross-exchange rates, filters markets to configured venues, and keeps minute-level snapshots to score how consistently each asset appears at different confidence levels. The execution pipeline checks existing positions, verifies current opportunities, asks an AI model to assess them, and then opens or closes paired positions.
Before opening trades, the workflow compares recent price spreads using synchronized candle data and estimates entry, exit, and round-trip costs from live quotes. The document illustrates the idea with a positive funding-rate example in which a short on the higher-rate venue is paired with a long on the lower-rate venue. It also describes position reversal and disappearance as exit conditions. This is an implementation outline, not performance evidence: it gives no measured returns or backtest results. It notes that spread moves, slippage, exchange and smart-contract failures, and capital split across venues can undermine the hedge; funding income is not guaranteed.
Key ideas
- Funding arbitrage seeks to collect the difference between venues’ perpetual funding rates using offsetting long and short positions.
- Minute-level snapshots and confidence-frequency scores are used to screen for opportunities that persist over time.
- Historical cross-venue spread behavior and live quote costs are checked before trades are opened.
- Positions are closed when an opportunity disappears or its preferred direction reverses.
- Spread volatility, execution costs, venue failures, and capital fragmentation can erase expected funding gains.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.