How to Use ME10012: Liquidation Risk in Trading

Liquidation data reveals price magnets and cascade risk. Essential for leverage management.

Strategy 1: Liquidation Magnet Trading

def find_magnets():
    """Find liquidation clusters that attract price."""
    heatmap = requests.get(f"{MADJIK_API}/metrics/ME10012/heatmap/now", headers=HEADERS).json()
    
    btc_price = 100000  # From price feed
    clusters = [l for l in heatmap["data"] 
               if l["total_usd"] > 100e6 and abs(l["price"] - btc_price) / btc_price < 0.1]
    
    if clusters:
        target = max(clusters, key=lambda x: x["total_usd"])
        return {
            "signal": "LIQUIDATION_MAGNET",
            "target_price": target["price"],
            "amount_at_risk": f"${target['total_usd']/1e6:.0f}M"
        }
    return {"signal": "NO_SIGNIFICANT_CLUSTERS"}

print(find_magnets())

Strategy 2: Cascade Risk Management

def cascade_check():
    """Check cascade probability before using leverage."""
    cascade = requests.get(f"{MADJIK_API}/metrics/ME10012/cascade/now", headers=HEADERS).json()
    
    prob = cascade["value"]
    
    if prob > 70:
        return {"max_leverage": "1x", "warning": "CASCADE IMMINENT - spot only"}
    elif prob > 50:
        return {"max_leverage": "2x", "warning": "Elevated risk"}
    return {"max_leverage": "5x", "status": "Normal"}

Risk Matrix

For informational purposes only. Not financial, investment, tax, legal or other advice.