Portfolio Rebalancer

# Live API output — March 12, 2026
Market Regime: Mean-Reverting
Safety Score: 96.2 (HIGH)

Composite Signals:
  BTC: buy (score: 0.172)\n  ETH: buy (score: 0.228)\n  SOL: buy (score: 0.219)\n  HYPE: strong_buy (score: 0.371)\n
# The bot would use this data to make trading decisions

import requests

API_KEY = "YOUR_API_KEY"
BASE = "https://algotick.dev"

def get_target_allocation():
    """Signal-driven portfolio rebalancer using composite and regime."""
    composite = requests.get(f"{{BASE}}/v1/signals/composite",
                            params={{"api_key": API_KEY}}).json()
    safety = requests.get(f"{{BASE}}/v3/signals/safety",
                         params={{"api_key": API_KEY}}).json()

    coherence = safety.get("coherence_score", 50)
    cash_weight = max(0.1, 1 - coherence / 100)  # More cash when signals disagree

    allocations = {{}}
    for sig in composite.get("signals", []):
        coin = sig.get("coin")
        score = sig.get("composite_score", 0)
        regime = sig.get("regime", "neutral")

        # Score-weighted allocation
        weight = max(0, (score + 1) / 2)  # Normalize -1..1 to 0..1
        if "mean" in regime.lower():
            weight *= 0.5  # Reduce size in mean-reverting regimes
        allocations[coin] = weight

    # Normalize
    total = sum(allocations.values()) or 1
    risk_budget = 1 - cash_weight
    for coin in allocations:
        allocations[coin] = (allocations[coin] / total) * risk_budget

    allocations["CASH"] = cash_weight

    print("\nTarget Allocation:")
    for coin, weight in sorted(allocations.items(), key=lambda x: -x[1]):
        print(f"  {{coin}}: {{weight*100:.1f}}%")

get_target_allocation()

# All endpoints used by this template:
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v3/signals/regime
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v1/signals/composite
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v3/signals/safety
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v1/signals/volatility?coin=BTC