# Real Estate Appreciation Rate Using Percent Change from Normal Distribution Curve

Good morning and good news! I woke up this morning and started working on adding in some additional ways to randomize variables in the Nomad Calculator 3.

Earlier this month, I added the ability to set a House Variable to a random number between a high and low. With the way I previously coded it, for example, I could say the house price appreciation is somewhere between -5% per year and 5% per year (calculated monthly). This meant that each month you decided to run this Rule, the real estate portfolio modeling software, would pick a random number between -5% and 5% and set the appreciation rate equal to that.

As some of you might imagine, that meant that the results were erratic. You could have a month where your property went up in value at a rate of -5% per year (since we calculate it monthly though… it means it went up 1/12 of that for that month) but the very next month we could, if the random number gods made it so, have it go up 5%. For modeling reality, I found this highly unlikely when talking about appreciation. For things like modeling maintenance costs on a property, a truly random number between a range might be an acceptable way to model it. Of course, you can choose the range of random numbers, but still, it was completely random.

Back to appreciation rate though… when we are modeling appreciation rates, I think appreciate rates tend to trend. For example, if a property has been going up at about 3% per year, it will tend to continue to go up about 3% per year the next month. Maybe it is going up 2.9% or maybe 3.1% but it is not likely to be -5% the next month. To model this, I decided to add an additional way to model these which will be especially helpful when we do Monte Carlo modeling of real estate investing portfolios.

Now, with the new code, I pick a percentage change for appreciation rate based on a normal distribution curve. So, I might say the appreciation rate can change anywhere from -25% to 25% in any given month with the average being that it does not change at all. So, if it was at 4% and it changed -25%, that means the next month it could be as low as 3%. But, that is not super likely. It could also go up 25% so that the yearly appreciation rate was 5%. Again, that’s not super likely either. It is most likely to remain at 4% (a change of 0%). It is also relatively likely it will drop to something like 3.9% or go up to 4.1%.

I ran it on a Scenario I had been playing around with for modeling Nomad and here’s what the appreciation rates for a number of houses ended up being. As you may be able to see in the chart above, this shows appreciation rates that trend. Again, this is because we are adjusting the appreciation rate a percentage of what it was the previous month based on a normal distribution curve.