
Establish acquisition assumptions for a real estate model by listing address, gross leasable area, units, density, and tenant, and compute initial and reversionary yields from price, costs, and rental value.
Lower debt by modeling the loan amount with a 55 percent ltv. Include loan issuance fees, freeze panes, and an if formula tied to the drawdown and acquisition dates.
Explore how value appreciation adds to profitability and model acquisition, investment, and exit cash flows, including exit costs and loan repayment on exit.
Analyze the real estate investment model outcomes and offer an investment recommendation, noting lease expiry risk, price renegotiation, and leveraged returns driving the IRR toward 10%.
Learn how to analyze real estate investments in Excel and how to make investment recommendations based on your analysis. On this course you will have the opportunity to practice and become a true excel modelling wiz with the four cases included in the course materials.
The models you build will be completely automated and dynamic and will allow you to test your assumptions and run sensitivity analysis on your main investment assumptions.
If you are preparing for an interview for both real estate investment and asset management roles, this course will help you pass the Excel test that is the first stage on the interview process, because it is based on modeling exercises that I have done as part of recruiting processes.
To get the most out of this course you need previous knowledge of Excel and finance, including among other the use of formulas such as EDATE, SUMIF, INDEX, MATCH, and finance concepts related to revenue, costs, profitability and returns, such as the IRR, equity multiple, cash on cash returns and gross and net initial yields.
It's also good to have some knowledge on debt financing such as loan to value, ratios and financial solvency such as debt yield, debt service coverage ratio and interest coverage ratio.