Every time we underwrite a new asset, we build models. But modeling an apartment building isn’t like modeling a house. The price isn’t just what someone thinks it’s worth; it’s determined by net operating income and cap rates, which are heavily influenced by interest rates.

Modeling for apartment investing also includes measures of job and population growth in a given area and the impact of new construction. Suffice it to say, underwriting major real estate assets is pretty complicated.

The funny thing is that even the inputs we use in our models are based on other models. So, essentially, you have models based on models. For instance, central banks use models to manage inflation, predicting the effects of monetary policies. In the corporate world, businesses use models to forecast demand, optimize pricing strategies, and manage supply chains. These variables directly influence our underwriting models.

Herein lies the limitation of modeling: it depends on the accuracy of the input data. Models are only as good as the data fed into them; inaccurate or incomplete data can lead to misleading results. So, if the models generating the numbers for your models are off, then your model is off as well. So why do we do it anyway?

Well, it’s the best we can do, and most of the time, in my experience, the modeling points us in the right direction.

On this week’s episode of Wealth Formula Podcast, I interview Doug Howarth. He’s developed a unique approach to economic modeling called Hypernomics. He shares his insights on how Hypernomics can uncover hidden dimensions in markets and provide deeper understandings and strategic advantages.

04:40 What is Hypernomics?

11:21 Application Towards Real Estate Investing