Define Your Objective: Before starting your model, understand what you want from it. Are you evaluating a potential acquisition, or are you examining the impact of refinancing an existing property?

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Gather Historical Data: Accumulate all financial data related to the property. This includes rent rolls, previous years' income statements, balance sheets, and capital expenditures.

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Input Revenue Assumptions:

• ‍Rent: Project the future rental income, considering current market rates, potential rent hikes, and expected occupancy rates.
• ‍Other Income: Include other revenue streams, such as laundry, parking, or other amenities.

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Detail Expense Assumptions: This includes:

• ‍Operating Expenses: Maintenance, property management fees, insurance, taxes, utilities, etc.
• ‍Capital Expenditures: Costs for property improvements or significant repairs.
• ‍Debt Service: If you're considering financing, add your monthly loan payments.

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Determine the Net Operating Income (NOI):‍

NOI = Total Revenue − Total Operating Expenses

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‍Factor in Debt Service: Subtract any loan payments from the NOI to get your net income or cash flow.

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Calculate Key Metrics:

• ‍Cash-on-Cash Return: This metric gives you the annual return on your investment based on the cash income earned on the cash invested.
• ‍Capitalization Rate (Cap Rate): A ratio that helps evaluate a real estate investment's profitability.
• ‍Internal Rate of Return (IRR): An estimate of the property's potential long-term return.

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Scenario Analysis: Model various scenarios, including best-case, worst-case, and most likely case. This helps prepare for different market conditions and provides a range of possible outcomes.

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Exit Strategy: Finally, forecast the potential sale price of the property if you plan to sell it in the future. Use this along with the accumulated equity and debt repayment to determine the potential profit or loss upon sale.

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Review and Iterate: Once your model is complete, review it thoroughly. Financial modeling is as much an art as a science. Continuously refine your assumptions based on new information and trends to keep the model relevant.