How long did it take you to become comfortable w underwriting?

Just started a role as an acquisitions analyst intern, first experience within the real estate realm. Was kinda just tossed into the deep end with some beefy models. Curious to see in general how long it took some to become proficient with the entire process.

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After 9-12 month you should be able to model things on paper pretty easily / quickly. But it takes years to really zoom out and look at underwriting from a higher level.

For example, a broker tells me they want this price for a property in X submarket. I know rents in that submarket max out around $Ypsf, the deal will never work at the price they want and i know not to even waste my time modeling it out. Age of property and what that means for your all in basis (heavier rehabs might seem like an attractive purchase price, but your yield on total cost might be worse than just buying a core deal), rental spread to better stock in the submarket, how fast you can dig yourself out of negative leverage, discounted exit value vs where things are trading today, these are just a few of numerous factors that you need to think about and will just come with time. 

 
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If you are brand new to real estate then it'll take some time to know WHAT to model rather than the process of modeling itself. If you don't know that you would need to look for how the county/state reassess RET after a development or rehab then your model will be inaccurate. You would need to know what amenities can give premiums to rent to get more accurate forecasted rents. What the general spreads are for debt terms over SOFR/10-Year and what are some solid basic assumptions for leverage. Along the same lines what you should model for costs and fees in closings of loans, acquisitions, dispositions, equity raises, etc.. Some people can pick it up in like 6 months and look at an OM and know a good deal when they see it and others might take 18 months. I would focus less on the model itself and more on what inputs to put into it. People can create big complicated looking models that have a million inputs or simple models that just have the necessities, knowing what should go into it and what are reasonable assumptions will help you know what to look for and catch oversights before you send it off to whoever you report to. 

 

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