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August 18, 2006 at 8:45 AM in reply to: Iraq is like the housing market – but not like you think #32312
(former)FormerSanDiegan
Participant“Home Prices in Deep Freeze” -CNN,
LA Times, NY Times, SD U-T all claiming that sales are off and prices are coming down.It’s being spread everywhere as if it were true. Major media outlets are now saying that the bubble is losing steam. Should we believe these mainstream media rumour-mongers ?
Perhaps, sometimes we should.
ParticipantJES –
You are correct that the overall numbers were up 10-30% in general and are now negative in the cited areas. It’s pretty clear in the data that there was a break point sometime in 2005 for some areas.
Generally I agree with your assessments on points 1,2 , 3, &4. But be very very careful when parsing down to the zip code level.
Consider that DQ reported that La Jolla was up 66.8 % in May 2006 over May 2005. And that was on 26 sales!
UP 66.8% WOW !Dozens of sales in a single month still may not be enough in some cases. You need to smooth out the month-to-month variations.
You can find the numbers from past years as published in the U-T (data from DQ) on the web:
http://realestate.signonsandiego.com/area_homesales/pastyears.phpWe should either average over longer periods/larger regions, or consider the time history to get a feel for the amount of variation. The chart below gives a feel for the flucuation in a few of the areas. This is the median price for select zip codes in La Jolla, Point Loma and Poway.
Notice that the fluctuations about the trend lines that I placed are up to +/-20%. I drew in the trend lines to correspond to June-June for each year (Chart covers June 04 through June 05).
As a side note, the coastal zip codes appear to have topped out well before Poway, where the trend (in the rear-view mirror of the median price) was still rising in 2006 and the downturn there will likely just begin to show up over the next few months.
[img_assist|nid=1248|title=Selected Median Prices|desc=|link=node|align=left|width=400|height=300]
ParticipantOne of the real problems is that Monthly Year-over-year numbers are very noisy. Forget for the moment the previously discussed flaws in the median versus Case-Shiller or other index.
The following will be true for any monthly index.Problem #1. You are starting with a monthly number that varies a lot because of small sample size.
Problem #2. You are taking a difference of two different monthly numbers. Anyone who took (or more precisely remembers ) statistics can tell you that differencing two noisy estimates results in an even noisier estimate.
Example.
The monthly yeay-on-year change in 92106 (Point Loma) for July ’06 according to DQnews was -26%. However, for June ’06 this number was +7.9%.Last month would we be asking why and trying to explain why the price in Point Loma is still increasing ???
Be careful when considering these monthly numbers to justify anything.
ParticipantWhy not wait 4-6 months ?
Just track this condo “convo” complex for a few months. Even in the best of times (1998-2005) prices did not increase much in the last half of the year.
Watch this like a hawk for 4-6 months and see how far prices move, then make the decision.
ParticipantSD @ 20K not 10K
The graph shows SD inventory at 20,397, not 10K.
The labels are above the very faint axes making it difficult to read. However, when you select a particular metro area the actual number shows up at the top of the page in the figure title.
OC inventory : 15,990
LA inventory : 80,129LA is 4x SD inventory. The population ratio for the LA vs SD is probably > 4x (not sure precisely how it’s defined), so anticipate that the per capita inventory is closing in on SD.
ParticipantPoint Loma is South of the 8.
Definitely would not ever want to live there (tongue-in-cheek).But, lets forget about desirability, for a moment. The answer to the original post is … (drum roll please) ….
1. J.O.B.S.
&
2. SALARYParticipantPS –
I look forward to seeing the data, and hope that you can keep us updated as it progresses.
Also, if you also find any source for a longer historical record of inventory numbersthat would be useful. DQnews seems to have records back to 1988 (as mentioned in an article cited in the “Southland Home sales…” post), but I cannot find the records.
ParticipantInteresting tidbits from this article:
Monthly Carrying Costs
The typical monthly mortgage payment that Southland buyers committed themselves to paying was $2,437 last month, the same as the previous month and up from $2,052 a year ago. Adjusted for inflation, current payments are about 6.2 percent above typical payments in the spring of 1989, the peak of the prior real estate cycle.
Interesting that we are ~ 6% above the last peak in this number. I’d like to see a long-term plot of monthly mortgage cost over the last two SD or SO Cal real estate cycles.
Anyone know where we might find ?
Statistical Anomaly … Not
The article has the following statement “Southland sales have declined for eight consecutive months on a year-over-year basis.” followed by a comment that the drop may be “nothing more than a statistical blip,”
Doesn’t the first comment indicate that it’s a trend. A statistical blip would be a data point that deviates from the trend, not one that confirms it. What a dope !Participant“Note: I noticed that CTX and LEND both had extrodinary advances in the market today. Who are these investors? I have a bridge I’d like to sell them.”
Maybe the short sellers are buying the shares to lock in their profits. Not sure you want to sell a bridge to those guys.
ParticipantPS –
My median price example was not meant to counter your emerging approach for timing, I just want to help you out by pointing out that whatever factor(s) you use may have a seasonal pattern to them.
Accounting for these factors will help avoid buying on a “local maximum” or “local minimum” in the signal you are monitoring.
Months of inventory takes in two factors : number of sales and number of properties on the market. Both of the underlying factors (sales & # of homes for sale) will have seasonal variations that must be taken into account.
For the record I think you CAN determine when you are in the neighborhood of a bottom or peak in real estate. However, I don’t think it matters much in the long run (10 years)if you hit it 5% too soon or 5% too late, as long as you buy at a time when the relative costs of renting vs buying are relatively close.
I don’t think you can hit anything within 1-2% (or even know whether you’ve hit it within 1%) when the variations are in the 1-2% range.
ParticipantSDR – you missed several other intended misspellings and grammatical misgivings (including my misspelling of grammar) … as well as the sarcasm intended.
I was just trying to stop this glass-throwing from inside rock houses.
ParticipantWhyle Im not one too pick on grammer, what’s even more funnier is that VCJIM misspelled the word “mispelled.”
ParticipantSeasonal fluctuations in San Diego.
Below is an example had sitting around on my PC. I have been tracking the median price since shortly after I purchased in SD in 2Q 1996. Admittedly not the best indicator, but it is what I started tracking in my youth as a new homeowner.
I’m sure this is full of flaws, but it illustrates that the seasonal cycle can be quite strong. This chart shows the average monthly increase for the PRECEEDING 6 month period. Averaged over the last 7 years. TO interpret: The average percentage monhtly increase from Jan-June has been approximately 2% per month during this boom (cumulative 12% over the first half of the year). However, prices were flat over roughly the last half of the year ( ~ 1/2% per month or cumulative ~3%).
I would suspect that other indicators will have similar cycles that make it more difficult to identify the long-term trend from seasonal trend.
[img_assist|nid=1217|title=seasonal trend – Central San Diego|desc=|link=node|align=left|width=400|height=300]
ParticipantAN – I agree that catching the absolute bottom is difficult, as is catching the absolute top.
I sold a rental prop in 2001 when the numbers I tracked such as the publicized “affordability” number was in the teens (~ 15%?), very close to the low hit in the previous peak. Boy was I wrong.PS –
Another complication is the seasonal cycle. I know that the seasons in SD have more to do with June gloom and the amount of sunlight there is in the day than Autumn leaves and Winter chills.However, there are very strong seasonal cycles in SD real estate. This adds “noise” to your measurement and you must be aware of these in any timing model.
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