Perp Funding Basis

2. Funding Rate Signal Framework

Funding rate regime detection:

def funding_regime(rates_7d):
    """Classify funding rate regime from 7-day history."""
    avg = sum(rates_7d) / len(rates_7d)
    consecutive_positive = all(r > 0 for r in rates_7d[-3:])
    consecutive_negative = all(r < 0 for r in rates_7d[-3:])

    if avg > 0.03 and consecutive_positive:
        return "overheated_long"       # High risk of long squeeze
    elif avg > 0.01 and consecutive_positive:
        return "bullish_carry"          # Good carry trade environment
    elif avg < -0.02 and consecutive_negative:
        return "overheated_short"       # High risk of short squeeze
    elif avg < -0.005 and consecutive_negative:
        return "bearish_carry"          # Inverse carry trade
    else:
        return "neutral"

3. Spot-Futures Basis Analysis

Basis = Futures price - Spot price

For dated futures (quarterly), basis reflects cost-of-carry expectations:

# Annualized basis
def annualized_basis(futures_price, spot_price, days_to_expiry):
    basis_pct = (futures_price - spot_price) / spot_price
    annualized = basis_pct * (365 / days_to_expiry)
    return annualized

# Example: BTC spot $65,000, quarterly future $66,500, 45 days to expiry
# Basis: 2.31%, Annualized: 18.7%

Basis signal interpretation:

4. Cash-Carry Arbitrage (Delta-Neutral)

Strategy: buy spot + sell perpetual futures → collect funding rate

# Cash-carry trade P&L
def carry_trade_pnl(spot_entry, funding_rates, position_size):
    """
    Delta-neutral carry: long spot + short perp
    P&L comes purely from funding rate collection.
    """
    total_funding_collected = 0
    for rate in funding_rates:
        if rate > 0:  # Longs pay shorts → we collect as short
            total_funding_collected += rate * position_size
        else:  # Shorts pay longs → we pay as short
            total_funding_collected += rate * position_size  # This is negative

    return total_funding_collected

# Example: $100,000 position, avg funding +0.015% per 8h, 30 days
# Revenue: 0.015% × 3 × 30 × $100,000 = $1,350 (16.2% annualized)

Carry trade execution on OKX:

1. Buy spot BTC-USDT on OKX spot market
2. Open equal-sized short BTC-USDT-SWAP on OKX perpetual
3. Net delta = 0 (spot long cancels perp short)
4. Collect positive funding rate every 8 hours
5. Close both legs when funding rate turns negative or basis compresses

Risk factors:

• Funding rate can flip negative → carry becomes a cost
• Liquidation risk on short perp if insufficient margin (use 3-5x max leverage)
• Exchange counterparty risk (keep position across 2-3 exchanges)
• Basis can widen further before mean-reverting → mark-to-market loss on short leg

5. Cross-Exchange Funding Arbitrage

Different exchanges have different funding rates for the same asset. Arbitrage the spread:

# Example: BTC-USDT perpetual funding rates
exchange_rates = {
    "OKX": 0.015,       # +0.015% per 8h
    "Binance": 0.020,   # +0.020% per 8h
    "Bybit": 0.025,     # +0.025% per 8h
}

# Strategy: short on highest funding (Bybit) + long on lowest funding (OKX)
# Net carry = 0.025% - 0.015% = 0.010% per 8h
# Annualized: 0.010% × 3 × 365 = 10.95%
# Risk: execution cost + potential for rates to converge/flip

6. Funding Rate as Directional Indicator

Divergence signals (most powerful):

Historical pattern statistics (BTC):

• Funding > +0.05% for 3+ consecutive periods → 70% probability of a 5-10% correction within 7 days
• Funding < -0.03% for 3+ consecutive periods → 65% probability of a 5-15% bounce within 7 days
• These are contrarian signals; funding rate extremes indicate crowded positioning

7. Open Interest × Funding Rate Matrix

# Combined OI + Funding signal
def oi_funding_matrix(oi_change_24h_pct, funding_rate):
    if oi_change_24h_pct > 5 and funding_rate > 0.03:
        return "leveraged_long_buildup"    # High risk, squeeze potential
    elif oi_change_24h_pct > 5 and funding_rate < -0.01:
        return "leveraged_short_buildup"   # Short squeeze potential
    elif oi_change_24h_pct < -5 and funding_rate > 0:
        return "long_liquidation"          # Forced long closing
    elif oi_change_24h_pct < -5 and funding_rate < 0:
        return "short_liquidation"         # Forced short closing
    elif abs(oi_change_24h_pct) < 2 and abs(funding_rate) < 0.005:
        return "quiet_market"              # Low conviction, wait
    else:
        return "mixed"

Data Access

Via OKX API

# Funding rate history
# GET /api/v5/public/funding-rate-history?instId=BTC-USDT-SWAP

# Current funding rate
# GET /api/v5/public/funding-rate?instId=BTC-USDT-SWAP

# Open interest
# GET /api/v5/public/open-interest?instType=SWAP&instId=BTC-USDT-SWAP

Use load_skill("okx-market") for OKX data retrieval patterns.

Key Metrics to Track

Output Format

## Funding Rate & Basis Analysis — [Asset]

### Current Funding Rates
| Exchange | 8h Rate | Annualized | Regime |
|----------|---------|------------|--------|
| OKX | +0.015% | +16.4% | bullish_carry |
| Binance | +0.020% | +21.9% | bullish_carry |

### Basis Structure
- **Spot price**: $XX,XXX
- **Perp price**: $XX,XXX (premium: X.XX%)
- **Quarterly futures**: $XX,XXX (annualized basis: X.X%)
- **Basis regime**: [contango / flat / backwardation]

### Funding History (7-day)
- **Average**: +X.XXX%
- **Trend**: [rising / stable / declining]
- **Consecutive direction**: [X periods positive/negative]

### Open Interest
- **Current OI**: $X.XB
- **24h change**: [+/-X%]
- **OI × Funding signal**: [leveraged_long_buildup / quiet / etc.]

### Carry Trade Opportunity
- **Best carry**: [short on Exchange X, long spot]
- **Expected annualized yield**: X.X%
- **Risk**: [funding flip probability, liquidation distance]

### Directional Signal
- **Funding regime**: [overheated / bullish / neutral / bearish / oversold]
- **Divergence**: [none / bullish / bearish]
- **Confidence**: [high / medium / low]

Notes

• Funding rates are exchange-specific; always compare across OKX, Binance, and Bybit for the full picture
• Extremely high funding rates are a cost for longs, not a bullish signal — they indicate overcrowded positioning
• Cash-carry trades have execution risk: slippage on entry/exit, funding rate flipping, and exchange downtime during volatility
• Basis and funding rate signals work best when combined with on-chain data (MVRV, exchange flows)
• This framework is for research purposes only and does not constitute investment advice