Investment Analytics Guide

cap_rate = (Net Operating Income / Property Price) * 100
 
# Example
annual_rent = 24000
operating_expenses = annual_rent * 0.30  # 30% rule
noi = annual_rent - operating_expenses
property_price = 300000
 
cap_rate = (noi / property_price) * 100  # 5.6%

annual_cash_flow = noi - annual_debt_service
cash_invested = down_payment + closing_costs
 
cash_on_cash = (annual_cash_flow / cash_invested) * 100

grm = property_price / annual_rent
 
# Lower GRM = better deal
# Typical GRM: 8-15 depending on market

from propapis import PropAPIS
 
api = PropAPIS(api_key='your_api_key')
 
def analyze_investment(address):
    # Get property data
    prop = api.platforms.zillow.get_property(address)
 
    # Investment parameters
    purchase_price = prop.price
    annual_rent = prop.rent_zestimate * 12
 
    # Financing (80% LTV, 6.5% interest, 30-year)
    down_payment_pct = 0.20
    interest_rate = 0.065
    loan_term_years = 30
 
    down_payment = purchase_price * down_payment_pct
    loan_amount = purchase_price - down_payment
 
    # Calculate monthly payment
    monthly_rate = interest_rate / 12
    n_payments = loan_term_years * 12
    monthly_payment = loan_amount * (monthly_rate * (1 + monthly_rate)**n_payments) / ((1 + monthly_rate)**n_payments - 1)
 
    annual_debt_service = monthly_payment * 12
 
    # Operating expenses (30% rule)
    operating_expenses = annual_rent * 0.30
 
    # Calculate metrics
    noi = annual_rent - operating_expenses
    cap_rate = (noi / purchase_price) * 100
    annual_cash_flow = noi - annual_debt_service
    cash_on_cash = (annual_cash_flow / down_payment) * 100
    grm = purchase_price / annual_rent
 
    # Print analysis
    print(f"Investment Analysis: {prop.address}")
    print(f"\nProperty Details:")
    print(f"  Purchase Price: ${purchase_price:,}")
    print(f"  Annual Rent: ${annual_rent:,}")
    print(f"  Bedrooms: {prop.bedrooms} | Sqft: {prop.sqft:,}")
 
    print(f"\nFinancing:")
    print(f"  Down Payment (20%): ${down_payment:,}")
    print(f"  Loan Amount: ${loan_amount:,}")
    print(f"  Monthly Payment: ${monthly_payment:,.0f}")
 
    print(f"\nIncome & Expenses:")
    print(f"  Annual Rent: ${annual_rent:,}")
    print(f"  Operating Expenses (30%): ${operating_expenses:,.0f}")
    print(f"  Net Operating Income: ${noi:,.0f}")
    print(f"  Annual Debt Service: ${annual_debt_service:,.0f}")
    print(f"  Annual Cash Flow: ${annual_cash_flow:,.0f}")
 
    print(f"\nInvestment Metrics:")
    print(f"  Cap Rate: {cap_rate:.2f}%")
    print(f"  Cash-on-Cash Return: {cash_on_cash:.2f}%")
    print(f"  GRM: {grm:.1f}")
    print(f"  Monthly Cash Flow: ${annual_cash_flow/12:,.0f}")
 
    # Investment recommendation
    if cap_rate >= 7 and cash_on_cash >= 8:
        print(f"\n✓ STRONG INVESTMENT")
    elif cap_rate >= 5 and cash_on_cash >= 5:
        print(f"\n○ MODERATE INVESTMENT")
    else:
        print(f"\n✗ WEAK INVESTMENT")
 
    return {
        'cap_rate': cap_rate,
        'cash_on_cash': cash_on_cash,
        'monthly_cash_flow': annual_cash_flow / 12
    }
 
# Analyze property
metrics = analyze_investment('123 Main St, Austin, TX')

def compare_markets(markets):
    results = []
 
    for market in markets:
        # Get market data
        data = api.platforms.zillow.get_market_trends(location=market)
 
        # Get sample properties
        listings = api.platforms.zillow.search_listings(
            location=market,
            property_type='Single Family',
            max_results=50
        )
 
        # Calculate average cap rate
        cap_rates = []
        for prop in listings:
            if prop.rent_zestimate and prop.price:
                annual_rent = prop.rent_zestimate * 12
                noi = annual_rent * 0.70  # After expenses
                cap_rate = (noi / prop.price) * 100
                cap_rates.append(cap_rate)
 
        avg_cap_rate = sum(cap_rates) / len(cap_rates) if cap_rates else 0
 
        results.append({
            'market': market,
            'median_price': data.median_price,
            'growth': data.yoy_change,
            'avg_cap_rate': avg_cap_rate
        })
 
    # Rank by investment score
    for r in results:
        r['score'] = r['avg_cap_rate'] + (r['growth'] / 2)
 
    results.sort(key=lambda x: x['score'], reverse=True)
 
    print("Market Investment Rankings:")
    for i, r in enumerate(results, 1):
        print(f"{i}. {r['market']}")
        print(f"   Cap Rate: {r['avg_cap_rate']:.2f}% | Growth: {r['growth']:+.1f}%")
 
    return results

def find_undervalued_properties(market, discount=0.15):
    # Search active listings
    listings = api.platforms.zillow.search_listings(
        location=market,
        status='active',
        max_results=1000
    )
 
    undervalued = []
 
    for prop in listings:
        # Compare to Zestimate
        if prop.zestimate and prop.price < prop.zestimate * (1 - discount):
            discount_pct = ((prop.zestimate - prop.price) / prop.zestimate) * 100
 
            undervalued.append({
                'address': prop.address,
                'price': prop.price,
                'zestimate': prop.zestimate,
                'discount': discount_pct
            })
 
    # Sort by discount
    undervalued.sort(key=lambda x: x['discount'], reverse=True)
 
    print(f"Undervalued Properties in {market}:")
    for prop in undervalued[:10]:
        print(f"{prop['address']}")
        print(f"  Price: ${prop['price']:,} | Est: ${prop['zestimate']:,}")
        print(f"  Discount: {prop['discount']:.1f}%")
 
    return undervalued

from propapis import PropAPIS
 
api = PropAPIS(api_key='your_api_key')
 
# Get property for analysis
prop = api.platforms.zillow.get_property('123 Main St, Austin, TX')
 
# Quick metrics
cap_rate = (prop.rent_zestimate * 12 * 0.7 / prop.price) * 100
print(f"Quick Cap Rate: {cap_rate:.2f}%")