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JAOT

Real Estate Investment

Real estate investment optimization selects the best portfolio of properties from a candidate set, balancing expected annual yield against a fixed budget and property-type diversification constraints. The example below models binary property selection: given 7 candidates with known acquisition costs and expected yields, find the subset that maximizes total annual income within a $10M budget.

Step-by-Step Walkthrough

1. Define candidate properties

List each potential investment with its acquisition cost, expected annual yield (rental income / cost), risk rating, location, and property type (residential, office, retail, industrial).

2. Set budget and financing constraints

Define your total investment budget, maximum leverage ratio, and any financing restrictions. Include transaction costs and capital improvement requirements in each property's total cost.

3. Add diversification rules

Specify portfolio constraints:

  • Maximum allocation to any single market or city
  • Minimum number of property types in the portfolio
  • Maximum concentration in any single property
  • Geographic spread requirements

4. Set the objective

Typically maximize expected annual yield or maximize total portfolio value subject to budget and diversification constraints.

Real Estate Investment in JAOT Builder

5. Review the recommended portfolio

The solver identifies which properties to acquire. Compare the optimized portfolio against your team's shortlist. Adjust constraints (e.g., require at least one property in a target market) and re-run to explore alternatives.

Example Parameters

import httpx

API_URL = "https://jaot.io/api/v2"
headers = {"Authorization": "Bearer ok_live_your_key_here"}

# Select from 7 properties with a $10M budget
response = httpx.post(f"{API_URL}/solve", headers=headers, json={
    "variables": [
        {"name": "downtown_office", "type": "binary"},
        {"name": "suburban_apartments", "type": "binary"},
        {"name": "retail_plaza", "type": "binary"},
        {"name": "industrial_warehouse", "type": "binary"},
        {"name": "mixed_use_tower", "type": "binary"},
        {"name": "student_housing", "type": "binary"},
        {"name": "medical_office", "type": "binary"},
    ],
    "objective": {
        "sense": "maximize",
        "coefficients": {
            "downtown_office": 180000,
            "suburban_apartments": 155000,
            "retail_plaza": 120000,
            "industrial_warehouse": 95000,
            "mixed_use_tower": 250000,
            "student_housing": 110000,
            "medical_office": 140000,
        },
    },
    "constraints": [
        {
            "name": "total_budget",
            "coefficients": {
                "downtown_office": 2800000, "suburban_apartments": 2200000,
                "retail_plaza": 1500000, "industrial_warehouse": 900000,
                "mixed_use_tower": 4500000, "student_housing": 1800000,
                "medical_office": 2100000
            },
            "sense": "<=",
            "rhs": 10000000,
        },
        {
            "name": "max_office_exposure",
            "coefficients": {"downtown_office": 1, "medical_office": 1},
            "sense": "<=",
            "rhs": 1,
        },
        {
            "name": "min_properties",
            "coefficients": {
                "downtown_office": 1, "suburban_apartments": 1,
                "retail_plaza": 1, "industrial_warehouse": 1,
                "mixed_use_tower": 1, "student_housing": 1,
                "medical_office": 1
            },
            "sense": ">=",
            "rhs": 3,
        },
    ],
})
result = response.json()

print(f"Maximum annual yield: ${result['objective_value']:,.0f}")
for var in result["variables"]:
    if var["value"] > 0.5:
        print(f"  Acquire: {var['name']}")

Templates

  • Budget Allocation Optimizer -- adapt budget allocation to property investment selection with diversification constraints
  • Custom Optimization -- build a real estate portfolio model with your specific properties, markets, and investment criteria

Next Steps