Python
# Portfolio analysis framework
portfolio = {
    'FTSE_All_World': {'allocation': 70, 'ter': 0.22, 'accumulating': True},
    'MSCI_EM_IMI': {'allocation': 20, 'ter': 0.18, 'accumulating': True}, 
    'Euro_Government_Bonds': {'allocation': 10, 'ter': 0.12, 'distributing': False}
}

def analyze_german_tax_efficiency(portfolio):
    return {
        'vorabpauschale_impact': calculate_vorab(portfolio),
        'ter_drag': sum(etf['allocation'] * etf['ter'] for etf in portfolio.values()) / 100,
        'rebalancing_frequency': 'annual' if accumulating_heavy else 'quarterly'
    }

Progress:

• Asset Allocation Review: Check home bias, regional distribution
• Tax Optimization: Verify accumulating ETFs for Vorabpauschale benefits
• Cost Analysis: Calculate total TER drag and trading costs
• Broker Assessment: Ensure German tax reporting compliance
• Rebalancing Strategy: Set thresholds and frequency
• Emergency Fund Check: Verify 3-6 months expenses in cash

Step-by-Step Process

1. Document current holdings with ISIN, allocation %, TER, and accumulating/distributing status
2. Calculate geographic exposure - check for over-concentration in any region
3. Assess tax efficiency - prioritize accumulating ETFs to defer taxes via Vorabpauschale
4. Review broker setup - ensure automatic tax reporting to German authorities
5. Set rebalancing rules - typically when allocation drifts >5% from target

Example 1: Basic Three-Fund Portfolio Input: 25-year-old, €50k invested, moderate risk tolerance Output:

• 70% FTSE All-World (IE00BK5BQT80)
• 20% MSCI Emerging Markets IMI (IE00BKM4GZ66)
• 10% Euro Government Bonds (IE00B4WXJJ64)

Example 2: Tax Drag Calculation Input: €100k portfolio, 0.2% average TER Output: Annual cost = €200, after 20 years with 7% growth = €8,200 in lost compound returns