posted by : ThomasC on July 6, 2012
DataQuick tracks home sales nationwide weekly, and in our current report we found prices continue to rise, as they have for the past several months.
During the 30-day sales period ending July 5, approximately 211,000 homes were sold in 98 of the top 100 metropolitan statistical areas.
Sales overall rose 12% from the same period a year earlier and 10.6% from 2009 levels.
Home prices also went up with the median price hitting $193,000 on July 5, up 6% from a year ago and 4.3% from three years ago.
In a little over a month, the median sales price rose from $186,000 to $193,000. In a recent survey by Trulia, which was reported in the Wall Street Journal, home shoppers are seeing much lower inventory, which naturally leads to higher prices overall.
Our report analyzes over two-thirds of all U.S. home sales.
For more details, visit DQ News at www.dqnews.com.
posted by : ThomasC on May 31, 2012
We all know the factors that make your home more valuable - views, updated kitchen, proximity to the ocean or a lake (or the freeway, on the downside). But, distance from a Walmart as a predictor of home values?
Apparently so. CNNMoney has outlined a new study by economists Devin Pope at the University of Chicago and Jaren Pope at Brigham Young University that reveals 2 new Walmart stores may actually improve home prices near the store.
The report analyzed over 600,000 housing transactions nearby 159 new Walmart stores, which showed that homes within a half mile of a new store saw prices increase between 2.0 and 3.0 percent, an average of $7,000 in the two and a half years after a new Walmart store opened. Homes between a half mile and one mile away experienced price increases between 1.0 and 2.0 percent, an average of $4,000. The report notes that over one mile away, and the increases were “statistically insignificant.”
The report analyzed the pre-housing crash era, looking at transactions between 2001 and 2006, but did not include rural areas where housing data was unavailable, so further studies are definitely merited.
DataQuick's property research tools provide valuation reports as well as business, school and demographic reports. Maybe we need to add “proximity to Walmart” into the valuation equation? How about a Walmart's in a 5-mile radius report?
What do you think? Is the distance from a Walmart really a factor in determining the value of a property, or just a coincidence?
posted by : Yong Kim on February 23, 2012
Last week, we received our AVM test results from one of the largest banks in the U.S. To their credit, they are one of a few banks that periodically conducts their own AVM performance analysis, in order to better align their AVM cascade, rather than depending on vendor reported AVM performance results or relying on third party results.
The bank actually conducts their tests on two populations of loans: a population of recent purchase loans closed by the bank, and a population of closed refinance loans where the appraisal value is used as the benchmark. They do this since they only use AVM values to support their refinance activity. This is also very clever because it provides some visibility into which lenders may be gaming the third party testing process by way of MLS data, or access to recent sales data on the subject property.
It is widely accepted among AVM providers that third party tests can be easily gamed due to access to MLS data or known sales data in the test population, distributed by the testing firm, which consists of addresses of properties that have recently sold. In fact third party testers rely on the AVM vendors to not return valuation estimates when the actual sales price or listing price is known within their own database. Unfortunately this methodology places far too much reliance on the integrity of the vendors, resulting in large discrepancies between the reported performances versus the actual performance experienced during deployment in the real world. This behavior is very easily observed based on the test results we received last week.
Generally auto valuation models are built using sales comp data around the subject property. Consequently the accuracy should not vary by much, and should not depend on whether the subject property is listed for sale or not. In other words, a model should return the same valuation estimate on a property before or after a listing, and should not be influenced by the listing price of the subject property.
When we observe the test results however, the wide disparity between the accuracy achieved on the purchase loan population compared to refi loan population, among some vendors, is quite suspicious. This is especially evident among the models that perform very high on the purchase loan population while performing average or below average on the refi population. In fact 7 out of the 23 vendors had a 20 point or more discrepancy between the two test populations. As an example, I’m observing models that performed 81% within 10% on the purchase population, but achieving only 46% within 10% on the refi population. Another resulted in 81% vs 54% within 10%. (As an aside, you should question any AVM that is performing near 80% within 10% since most AVMs perform within 50 to 60% within 10%. This is statistically equivalent to finishing a 100 meter race under nine seconds – very suspicious!) Overall, although our AVM was not the first in both cases, I was pleased to see that we performed above average and very similarly on both tests.
posted by : ThomasC on February 14, 2012
I found an interesting quote in the 2012 State of the Industry Report put out by October Research and The Title Report.
“You could see title agents become debt negotiation firms,” Miller said. “They can actually delegate authority at certain levels to do resolutions to get deed in lieu transactions consummated on behalf of lenders or servicers. They’re actually allowed to go to certain levels to pay off seconds and all sorts of things.”
Interesting! Title companies and their agents could help consumate a deed in lieu transaction. The article goes on to point out other niches title companies could go after to help us get out of the distressed property and foreclosure mess.
What's your opinion? Is this part of the mandate of a title company, or just a novel idea?
Whatevever your opinion on the topic, DataQuick can help you identify properties in any form of distress - bank owned, recent short-sale, notice of default, notice of sale at auction (NOT). And, soon, DataQuick property research products will provide insight into lis pendens and deed in lieu of trust.
Please post your opinions, and thanks for reading our blog!
posted by : Yong Kim on January 26, 2012
I just came back from the ASF 2012 conference in Las Vegas. I have to admit, the first day (Sunday) was really all about football, but it was all business afterwards. Generally there seemed to be lot of activity and optimism this year (perhaps helped by the fact that the Giants are making another Super Bowl appearance). All the sessions appeared to be well attended, including the Wednesday morning sessions.
One session that was particularly of interest to me was on Securitization Data and Analytics Innovations. It was lead by Ned Meyers, SR. VP from Lewtan. On the panel were reps. from Bloomberg, Equifax, 1010Data, Morningstar, and LPS. Following are some highlights from the session:
- Equifax stated generally the biggest lift in the default models came from updated credit scores. I think this is little bit contrary to what Laurie Goodman has been touting which is that CLTV is the biggest determinant of default.
- Lewtan stated accurate property level valuations are critical for estimating losses. This may be obvious to those outside of the RMBS world, but identifying property level data has been unavailable until companies like us were able to figure out a way to match the data and is a fairly new best practice that is being adopted by more and more investors in this space.
- LPS stated that they definitely saw discounts on REO resales that helped estimate losses. Their method for estimating REO discounts is to use non-distressed HPI and compare against distress only sales.
- LPS stated according to their analysis the REO discount rate was generally the same across all geography. Our analysis, however, shows that there could be differences based on geography and is a function of market saturation.
- LPS displayed zip code level HPI heat maps of LA and NY with a simple message that MSA/CSA level HPI should not be trusted. It’s funny that these were the maps we were demonstrating two years ago. It’s good to see that our work is being validated by others as well.
- It appears that rating agencies are now taking a deeper interest in analyzing loan level and even property level data supporting the residential bonds that they are rating.
I would love to hear your impressions of the conference if you were able to attend.