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Just for fun, I wanted to take the pricing data stats from my previous post about market timing and apply a slow stochastic to the prices.

Here’s essentially how they work with stocks.

On the lower part of the image is an example of a slow stochastic. A buy signal is interpreted when the %k (green line) crosses up over the %d (white line). This is most important when value is crossing up from 30. A sell signal is the opposite. When %k is crossing down over %d from 75 (numbers on left). Go ahead and ignore the right numbers and red line for now. Essentially stochastics are trailing indicators of price trends. Trading decisions should never be made entirely from an indicator. It’s just an illustration of a trend over a time period. Depending on the time period you’re looking at, long-term and short-term trends can be identified.

Now, that being said. Here’s a slow stochastic showing short term (seasonal) market trends for the Denver Real Estate Market.

The stochastic demonstrates the change in price trends

, I smoothed the d by averaging 3 months of k. K represents a 3 month period. The price change may be subtle but savings of around 10k could be possible over the same house in the middle of summer. The change in color highlights where the trends change. You’ll notice that July of 2005 to February of 2006 was the longest down trend in recent history while November of 2006 was an earlier change trend change than usual. You’ll notice that the number of homes that sells varies greatly with the season. Periods of increased demand similar to 2004, demonstrate higher levels of homes sold in the spring and fall. Markets also vary greatly even within a city so it would be interesting to see how this worked in specific subdivisions. I’m also going to look into whether income properties differ from the residential home listings shown.

Feel free to contact me if you have any questions.

Technorati Tags: Denver, Real, Estate, Market, Timing, Stochastic, Price, Home, Value