CryptoFundingArb

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CryptoFundingArb

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Scans funding rates between CEX and DEX and displays the best opportunities

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# Funding-Rate Arbitrage Scanner

Scans six major crypto derivatives venues — **Binance, Bybit, OKX, KuCoin, Kraken, and Hyperliquid** — for **funding-rate arbitrage**: market-neutral trades that harvest the difference in perpetual funding rates for the same asset across exchanges. Unlike a naive spread scanner, it models **real trading costs** (fees, funding intervals, holding period) to report the **net** annualized return you could actually keep.

![Top funding-rate arbitrage opportunities: gross vs. net APR](https://raw.githubusercontent.com/hamood1337/CryptoFundingArb/main/docs/hero_chart.png)

> Gross APR (blue) is the raw funding spread. Net APR (green) is what survives after round-trip trading fees — the gap widens the shorter you hold, which is exactly the trade-off this tool makes explicit.

---

## What is funding-rate arbitrage?

Perpetual futures ("perps") have no expiry, so exchanges use a **funding rate** — a periodic payment between longs and shorts — to tether the perp price to spot. When funding is positive, longs pay shorts; when negative, shorts pay longs.

The same asset can have very different funding on different venues. If BTC funding is **+30% annualized** on Exchange A but **−10%** on Exchange B, you can:

- **Short** the high-funding leg (Exchange A) → *earn* funding
- **Long** the low-funding leg (Exchange B) → *pay less* funding

Your net exposure to BTC's price is roughly zero (**delta-neutral**), so you pocket the **funding spread** — here, ~40% annualized — regardless of which way BTC moves. This tool finds and ranks those spreads across venues, then tells you what's left after costs.

---

## Why this implementation is different

The interesting engineering is in turning a noisy, multi-venue data problem into a decision you can trust:

| Concern | How it's handled |
| --- | --- |
| **Net profit, not just spread** | Models per-venue maker/taker fees, computes **net APR** after a full round trip (open + close, both legs) and the **break-even holding time**. |
| **Interval-aware annualization** | Funding is charged on different cadences (Hyperliquid hourly, Binance every 8h). The same raw rate annualizes to wildly different APRs, so the interval is resolved per market — not assumed. |
| **Speed** | Uses each venue's **bulk** funding endpoint (one call for hundreds of symbols) where available, with a threaded per-symbol fallback for venues (KuCoin) that lack it. |
| **Cross-venue symbol matching** | Normalizes contract-size multipliers (`1000PEPE`, `1MBONK`, `kSHIB` → `PEPE`/`BONK`/`SHIB`) so the same underlying lines up across exchanges. |
| **Liquidity filtering** | Filters out thin markets by 24h quote volume so opportunities are actually tradeable. |
| **Resilience** | A venue that is down, rate-limited, or serving a malformed symbol is skipped with a warning — the scan still completes with the rest. |

---

## Architecture

The finance logic is completely decoupled from the network I/O, so the math is deterministic and unit-testable without ever hitting an exchange.

```
                 ┌─────────────┐
   ccxt / net ──▶│ exchanges.py│  I/O boundary: bulk + per-symbol fetch, retries
                 └──────┬──────┘
                        │ FundingSnapshot (immutable)
                 ┌──────▼──────┐
                 │  scanner.py │  orchestrate venues, degrade gracefully
                 └──────┬──────┘
                        │
        ┌───────────────┼────────────────┐
   ┌────▼────┐    ┌─────▼─────┐     ┌─────▼─────┐
   │funding  │    │arbitrage  │     │ fees.py   │   pure, no network
   │.py      │    │.py        │     │           │
   │annualise│    │pair+rank  │     │net PnL    │
   └─────────┘    └─────┬─────┘     └───────────┘
                        │ Opportunity (immutable)
                 ┌──────▼──────┐
                 │  render.py  │  rich tables · chart · JSON/CSV export
                 └─────────────┘
```

Every domain model is an immutable frozen dataclass; transformations return new objects rather than mutating in place.

---

## Installation

```bash
git clone https://github.com/hamood1337/CryptoFundingArb.git
cd CryptoFundingArb

python -m venv .venv && source .venv/bin/activate
pip install -e .          # installs the `fundingarb` command
```

Requires Python 3.10+. No API keys are needed — only public market data is used.

---

## Usage

```bash
# Default scan across all six venues
fundingarb

# Focus on the tradeable band and assume a 3-day hold (fees bite harder)
fundingarb --min-spread 20 --max-spread 300 --holding-days 3

# Only the fastest (bulk) venues, exporting results
fundingarb --exchanges binanceusdm bybit okx hyperliquid \
           --chart opportunities.png --export opps.csv
```

Everything also works without installing, via the compatibility shim:

```bash
python main.py --min-spread 10
```

### Options

| Flag | Default | Description |
| --- | --- | --- |
| `--min-spread` | `5.0` | Minimum gross APR spread (%) to report |
| `--max-spread` | none | Optional cap to hide ephemeral new-listing spikes |
| `--min-volume` | `1_000_000` | Minimum 24h quote volume (USD) per leg |
| `--holding-days` | `30` | Assumed holding period for net-APR amortization |
| `--exchanges` | all six | ccxt exchange ids to scan |
| `--maker-fees` | off | Cost with maker instead of taker fees (optimistic) |
| `--chart PATH` | — | Save a gross-vs-net bar chart |
| `--export PATH` | — | Export all opportunities to `.json` or `.csv` |
| `-v/--verbose` | off | Per-exchange logging |

### Sample output

```
146 opportunities  672 assets  6 venues  54.1s
              Top Funding-Rate Arbitrage Opportunities
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┓
┃ Asset   ┃ Long(pay) ┃ Short(earn)┃ Gross APR┃ Net APR ┃ Break-even┃ Min Vol  ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━┩
│ TAC     │ binance   │ bybit     │    283.1% │  257.5% │     0.3d  │  $47.6M  │
│ POWER   │ bybit     │ kucoin    │    246.8% │  218.8% │     0.3d  │   $1.6M  │
│ VANRY   │ kucoin    │ binance   │    232.4% │  205.6% │     0.3d  │  $22.3M  │
└─────────┴───────────┴───────────┴───────────┴─────────┴───────────┴──────────┘
```

An asset marked with `*` settles in different currencies on the two legs (e.g. USDT vs USDC) — a small extra basis risk worth noting.

---

## Methodology

For a raw funding rate `f` charged every `h` hours:

```
gross_apr   = f × (8760 / h) × 100                     # simple annualization, %
gross_spread = short_apr − long_apr                    # captured before costs
round_trip   = 2 × (taker_long + taker_short) × 100    # open + close, both legs, %
net_apr      = gross_spread − round_trip × (365 / holding_days)
break_even   = round_trip / (gross_spread / 365)       # days of funding to repay costs
```

**Notes & honest caveats.** APR is a *snapshot* annualization of the current funding print, so freshly-listed tokens can show enormous, short-lived numbers — use `--max-spread` to focus on the persistent, tradeable band. Fees default to public **taker** rates (conservative) and are configurable per account tier. The model doesn't include slippage, borrow costs, or the capital cost of margin on both legs.

---

## Testing

```bash
pip install -e ".[dev]"
pytest --cov=fundingarb
```

**87 tests, ~97% coverage.** The pure finance logic (annualization, fee math, pairing, ranking, symbol normalization) is exhaustively unit-tested; the ccxt adapter and orchestrator are tested against fakes so the suite runs offline in under a second.

---

## Roadmap

- [x] Filter out low-volume / illiquid tickers
- [x] Account for maker/taker fees across exchanges
- [x] Faster fetching (bulk endpoints + threaded fallback)
- [x] Test suite with high coverage
- [ ] Backtesting against historical funding series
- [ ] Entry/exit signals (e.g. funding mean-reversion bands)
- [ ] Live monitoring mode with alerts

---

## Credits

Huge thanks to [TheQuantStack](https://www.algos.org/) and [HangukQuant](https://hangukquant.com/) for invaluable information, tips, and code snippets. Highly recommended resources for anyone getting into the quant world.

## Disclaimer

This tool is for educational and informational purposes only. It is not financial advice. Funding-rate arbitrage carries real risks — execution slippage, funding-rate reversals, liquidation on either leg, and exchange counterparty risk. Always do your own research. The author is not responsible for any financial losses incurred from using this tool.

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