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sdduuuude
Participant“I didn’t get my car for $1000 below invoice without doing my research”
Cars aren’t just past the peak of a speculative bubble of epic proportions, either.
ParticipantOf course you are right, Bugs and PS, about the data – but I think the effect of this median going up will have the effect of a dead cat bounce – a little positive sentiment to fool the masses into thinking the worst is over just before the fecal matter collides with the air circulator.
I think alot of people are going to catch that falling knife in early 2007.
I know so many people who want to buy, have been waiting to buy, and think the bottom has hit. This median price uptick makes it impossible for me to talk them out of it.
ParticipantI know a guy who does lease-to-own deals.
He loves them, but I don’t think he discounts the monthly rent like that. He basically takes a deposit that allows the renter to buy the house at a specific price. If time goes on past a certain date, or if they stop paying rent, they lose the option.
If the buyer rents a while and walks away, he has some rental income and he the deposit is pure profit.
If the buyer rents for a while then buys, he has some rental income and he has sold the house at a profit.
ParticipantTold ya it was a dead cat bounce.
ParticipantI would like to place my vote for
“In God we Trust – Everyone Else Bring Data.”This was the motto for a long time and represents why Rich is so good at what he does.
Furthermore, it doesn’t make this strictly a “Bubble” site.
It is a Real Estate analysis site that will keep going even when the market is ready to grow again.
ParticipantIt may be an accepted principal when explaining the bubble that just burst, but not for estimating the bottom of the current one, except by those who understand bubbles but are clueless about statistics.
In your statement, you assume the bubble started in 2000, with no basis for the assumption, then go back 1 year, assuming that 1 year before your assumption is the right place to start. Then you come up with a number and it is close to your unsupported assumption, which makes you happy and leads you to believe your assumption is correct.
See, you have to wait for the bubble to stop bursting before you really know where it started. Then you say “it reverted to yada yada.” That’s reversion to the mean.
Your analysis so “freshman-in-college” I can’t believe it. Well, actually I can. I’ve come to expect it.
ParticipantReversion to the mean is typically used in retrospect to describe an event that has already happened. Using it for a forward-looking calculation is almost always destined for failure, especially in this case.
When data has a simple history of nice clean data around a fairly clear trend line (i.e. if the mean is the same no matter how far back in time you go), using reversion to the mean for a forward-looking estimate makes some sense.
However, if the mean of the last 5 years is different from the mean of the last 10 years is different from the mean of the last 50 years, the results of your reversion to the mean calculation are going to be basically random numbers.
Picking too short a timeframe means you don’t have a large enough number of samples. It also can ignore long term market effects.
Furthermore, the mean can revert to the data as well if your timeframe is too short. If I am looking at annual data and I choose a timeframe of 5 years, my next two datapoints are going to have a significant effect on the mean, even if the next two data points are the same as my 5th data point. If you wait long enough, eventually the mean will get very close to the data, even if the data does not change at all.
Picking too long a time frame ensures you have enough samples, but can underestimate the effect of any unusual short-term, current market conditions.
Secondly, picking the right variable is critical – is it prices? price growth? price growth relative to interest rates? prices relative to income? Interest rates themselves? Some combination of price, income and interest? Not all these variables can simultaneously revert to their means because they play off each other.
In the case of housing in the US, the tax anomaly in 1997 could have a drastic effect on the mean, so you have to be careful looking at data before then. But, that really isn’t enough time to get an understanding of what the mean is under these conditions. So, this is just an awful market in which to use this technique.
Finally, when data is random, we don’t know when the reversion will happen.
So, yes at some random time, something will revert to the mean of the last x years. Alot of good that does us.
Reversion to the mean is an analysis performed when they analyst doesn’t really know very many analytical techniques.
ParticipantBecause, powayseller, things take time.
Economies are slow-moving systems, measured in quarters and year-over-year comparisons.
People don’t just start mass layoffs because of a slow quarter. It is expensive to hire people, so you don’t just fire them if you don’t need them this week.
Also, keep in mind, the data we are getting now contains components from 4 (edited a typo) months ago.
Plus, your perception of the market is likely heavily influenced by your knowledge of San Diego, which is, as far as I can tell, pretty far ahead of the nation as far as the leaking bubble goes.
Your understanding of the market forces are pretty good, but your timing is a little fast.
ParticipantGreat post, cabinboy.
I think it was sensible, well-written advice based on 4 important but not well understood principals, and not one bit arrogant.
Participant“I think it will take 1-2 quarters more to slow down the consumer”
I think it could be several quarters away.
You speak of catalysts and massive layoffs as if you expect a true burst. As if the burst is an event, not a process. I see it as a small, unstoppable leak. There’ll be some layoffs this year. Some layoffs next year. Some more to follow after that, etc.
The catalysts are in place and slowly taking effect one-by-one. Not all at once.
Remember the boiling frog?
Sentiment is so hard to turn and that will delay the badness. People are talking about the real estate market recovering next year as if the bubble has burst. Meanwhile, the water gets warmer and warmer and warmer. It’s unbelievable.
ParticipantThis is my favorite powayseller thread ever.
That Roubini guy is alright. Very impressive to stick his neck out there and be right.
October 24, 2006 at 8:01 PM in reply to: 2 million foreclosures predicted in the coming months #38396ParticipantHey powayseller. I’m happy to have you back too. Never wanted you to disappear. Thanks for letting others take the reigns for a while. Much appreciated.
If 1 month of inventory is dumped on the market in 5 days, that’s a problem because it would double the months of inventory. If it gets dumped on the market over the course of 10 months, it isn’t so bad. The months of inventory would only be affected by 10%.
I’m not picking on PS, but on the article: The claim for an unspecified number of months doesn’t do anyone any good. How many friggin months is it?
ParticipantI’ve been gone for a few days – did I miss something or did she just disappear?
ParticipantThe canyon homes in Clairemont are a great value. The parts of Clairemont most poeople see are pretty low-end, but if you have someone who knows the ins and outs looking for you, you can find some great homes, especially with your budget.
I would always prefer those homes built in the 50s to any built in the 70s or later. The quality is excellent. You just have to find those areas with larger lot sizes, back in the canyons, away from the well-travelled streets.
Not sure what lindismith means by “getting in and out is for the birds.” Getting in and out of Point Loma is TERRIBLE compared to Clairemont. In PL, Your only choices are Nimitz and Rosecrans. You are stuck on a peninsula. Clairemont is surrounded by freeways. You have your choice of freeway access in any direction at any time and no freeway meters on Hwy 52.
If Clairemont is too cheap for you, consider UTC. You’ll get less home for the money, but it is a much nicer area and shares the central location of Clairemont.
Also, Bay Park and Bay Ho are nice. Lots of canyons and views of the bay. Sloped lots can lead to small yards, though, and the views will cost plenty.
The advantage of Bay Park, Clairemont and UTC over Point Loma = no airport noise, fewer overcast, foggy and misty days, less compact.
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