San Diego Resale Home Median Price: Actual vs. Fitted/Predicted

Robert Campbell, in his book, laid out that sales, interest rates, notices of default, etc. can be used to pick the best time to buy a house. Someone on the forum stated that RC did not use regression analysis to analyze his data.

I built on RC’s approach, using Minitab’s graphing, cross correlation, stepwise regression, and ordinary regression analysis functions, to arrive at a model for predicting San Diego resale home prices.

The graph above shows actual San Diego prices vs. those predicted by my model.

What I found is that price is a function of (1) time, (2) sales 6/18/24/30 months prior, (3) notices of default 18/24/36 months prior, 30 year fixed mortgage rates 6/24/30/36 months prior, and Fed funds rate today and 18/36 months prior.

Without a doubt, given the steep run up in prices, things may very well be different on the way down. But, I feel comfortable that the predictor variables make sense, and may give a ‘heads up’ that prices are on their way back up (5-10 years from now!), and that folks should get back in at the trough.

And, technically, if I was back in school, I would be in trouble for using all of the data that I had (monthly over ’88-’03) to arrive at my model, instead of using the first 80% of the data and then seeing if it fit using the remaining 20%. But, this is the real world, with money involved, so to heck with saving data!

What do you think?