Wednesday, December 15, 2010
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Tuesday, May 20, 2008
A Look at San Diego Average Home Prices 5/20/2008
Housing prices, pre-, in-, and post-bubble continue to be a hot topic. Rather than debate what prices “should” be, let’s observe what they are, how that relates to prior years, and if there are any reasonable expectations we might have for the near future. All price data comes from Sandicor’s monthly reports.
Figure 1a. San Diego County Average Priced Home
The timeline view in Figure 1a shows that average home price based on sales that closed in the given month. Figure 1b shows the same data in a year-over-year format. The price run-up really jumps out.
Figure 1b. San Diego County Average Priced Home – Year over Year
While that gives us status, where do today’s prices fit in with reasonable expectations of an increase in home prices over time? In the following figures, the average home price in January of each year is extrapolated at given growth rate. Figure 2a uses 8%. Figure 2b uses 5%.
Figure 2a. Housing Price Extrapolation at 8%
Depending on whom you listen to, home prices increase by 4-7% per year. In Figure 2a, we see that an 8% growth rate (compounded monthly), lines up fairly well for 2000, 2001, 2002, and 2008. If an 8% rate is appropriate for a major city, with perhaps the best weather in the country, that is limited by the ocean to the west, Camp Pendleton to the north, Mexico to the south, and the desert to the east, then today’s prices are about right where they should be.
Figure 2b. Housing Price Extrapolation at 5%
If however, you want to use a 5% growth rate, then today’s prices line up with the beginning of 2003, clearly in bubble territory. Coincidentally, 2007 prices line up with 2004 prices. In both figures 1b and 2b, we can see the jump in prices that occurred in 2002. If this view were correct, then the average San Diego home price is still too high by about $90K.
Admittedly none of this discussion considers the economics of supply and demand as imposed by lower interest rates and a credit crunch, by growth in bio-tech and tourism or a decline in construction and all related industries. Nor do we consider the many other variables that affect our markets.
Where will or should our prices be tomorrow? An 8% growth rate does not offend me, for which I would argue that prices should be up. However, the real estate cycle will naturally drive prices below where they should be until the masses recognize the great deals and take us back to the era of multiple-offers and rapidly escalating prices (thus repeating the cycle). Given that, I expect prices to slide a bit further, but there are already some great buys out there. We are seeing some prices less than 45-50% of their highs.
Figure 1a. San Diego County Average Priced Home
The timeline view in Figure 1a shows that average home price based on sales that closed in the given month. Figure 1b shows the same data in a year-over-year format. The price run-up really jumps out.
Figure 1b. San Diego County Average Priced Home – Year over Year
While that gives us status, where do today’s prices fit in with reasonable expectations of an increase in home prices over time? In the following figures, the average home price in January of each year is extrapolated at given growth rate. Figure 2a uses 8%. Figure 2b uses 5%.
Figure 2a. Housing Price Extrapolation at 8%
Depending on whom you listen to, home prices increase by 4-7% per year. In Figure 2a, we see that an 8% growth rate (compounded monthly), lines up fairly well for 2000, 2001, 2002, and 2008. If an 8% rate is appropriate for a major city, with perhaps the best weather in the country, that is limited by the ocean to the west, Camp Pendleton to the north, Mexico to the south, and the desert to the east, then today’s prices are about right where they should be.
Figure 2b. Housing Price Extrapolation at 5%
If however, you want to use a 5% growth rate, then today’s prices line up with the beginning of 2003, clearly in bubble territory. Coincidentally, 2007 prices line up with 2004 prices. In both figures 1b and 2b, we can see the jump in prices that occurred in 2002. If this view were correct, then the average San Diego home price is still too high by about $90K.
Admittedly none of this discussion considers the economics of supply and demand as imposed by lower interest rates and a credit crunch, by growth in bio-tech and tourism or a decline in construction and all related industries. Nor do we consider the many other variables that affect our markets.
Where will or should our prices be tomorrow? An 8% growth rate does not offend me, for which I would argue that prices should be up. However, the real estate cycle will naturally drive prices below where they should be until the masses recognize the great deals and take us back to the era of multiple-offers and rapidly escalating prices (thus repeating the cycle). Given that, I expect prices to slide a bit further, but there are already some great buys out there. We are seeing some prices less than 45-50% of their highs.
Sunday, April 27, 2008
Foreclosures and Short Sales in San Diego as of 4/27/08
We gave a homebuyer seminar this last Saturday, the 26th, and received several very good questions with respect to what we are experiencing in the short sale / foreclosure market. I thought everyone would like to know that although the market has been tough, you can’t just low-ball the bank and expect to walk away with a deal.
In summary, if you are serious about owning a home or investing, then…
When a property is 30% or more below where it was at the top of the market, it is probably a good deal, move quickly. When it is a short sale, your target is the current low list price or about 20% below its old list price, but be prepared to wait months before hearing back from the lender and don’t be surprised if you lose out on several opportunities. When you see a normal sale, aim for 10% below its list price and expect the properly priced properties to disappear in about a month’s time. Details and rationale below.
There are 18,673 homes or condos on the market.
There are 6,281 (33.6%) listed as short sales.
There are 942 (5%) listed as foreclosures.
Nearly 39% of our market is composed of distressed homes.
In 2007, there were 1,839 short sales that closed. This year, there are already 1,372 that have completed the process. That puts us on track to more than double last year. Everyone wants a deal; labeling a property as a short-sale brings out the bargain hunters. For two different buyers, we have attempted to put purchase offers on several properties only to find that every one we asked after already had multiple offers. The agents are merely waiting on the lenders to respond, which is taking 2 ½ to 4 months. We surmise off our few data points, that most short sales probably have multiple offers and only the bank delays are keeping them on the books. One can only surmise that our market would look much stronger if all these pending offers were completed sales.
Of the short sales that have been sold this year, the most interesting fact is that the median sales price is 99.8% of the low asking price (stdev=6.4%). That is to say that, on average, you should expect to pay the low asking price, as can be seen in the following histogram, broken down in 5% increments, labelled with the low end of each increment,
Having said that, the asking price tends to be reduced over time. The chart below shows the sales price divided by the old list price with respect to days on the market.
The median sales price comes in at 87.4% of the old list price (stdev=11.1%). The following histogram shows how sales prices compare to the old list price.
The absolute best sales price to old list price ratio was 50.9%, the median was 87.4%and the worst was 117.1%. The moral of the story... don’t put in a half price offer and plan to get anywhere.
The major differences between short sales and normal sales can be seen in the following table.
The most significant observation is that normal sales now tend to be pretty well-priced out the gate and are being purchased in less than 1/3 the time of a short sale. Of course, the time difference could merely be the delay in waiting on the lenders. Not surprisingly then, the sales price in a normal sale ends up being much closer to the asking price.
In conclusion... there are good buys out there and they are going quick. However, there are a ton of new listings that are still over-priced. So, look at the time on the market and check to see whether or not the price has already been reduced. Keep the above statistics in mind when making your offer.
In summary, if you are serious about owning a home or investing, then…
When a property is 30% or more below where it was at the top of the market, it is probably a good deal, move quickly. When it is a short sale, your target is the current low list price or about 20% below its old list price, but be prepared to wait months before hearing back from the lender and don’t be surprised if you lose out on several opportunities. When you see a normal sale, aim for 10% below its list price and expect the properly priced properties to disappear in about a month’s time. Details and rationale below.
There are 18,673 homes or condos on the market.
There are 6,281 (33.6%) listed as short sales.
There are 942 (5%) listed as foreclosures.
Nearly 39% of our market is composed of distressed homes.
In 2007, there were 1,839 short sales that closed. This year, there are already 1,372 that have completed the process. That puts us on track to more than double last year. Everyone wants a deal; labeling a property as a short-sale brings out the bargain hunters. For two different buyers, we have attempted to put purchase offers on several properties only to find that every one we asked after already had multiple offers. The agents are merely waiting on the lenders to respond, which is taking 2 ½ to 4 months. We surmise off our few data points, that most short sales probably have multiple offers and only the bank delays are keeping them on the books. One can only surmise that our market would look much stronger if all these pending offers were completed sales.
Of the short sales that have been sold this year, the most interesting fact is that the median sales price is 99.8% of the low asking price (stdev=6.4%). That is to say that, on average, you should expect to pay the low asking price, as can be seen in the following histogram, broken down in 5% increments, labelled with the low end of each increment,
Having said that, the asking price tends to be reduced over time. The chart below shows the sales price divided by the old list price with respect to days on the market.
The median sales price comes in at 87.4% of the old list price (stdev=11.1%). The following histogram shows how sales prices compare to the old list price.
The absolute best sales price to old list price ratio was 50.9%, the median was 87.4%and the worst was 117.1%. The moral of the story... don’t put in a half price offer and plan to get anywhere.
Short Sales and Normal Sales
The major differences between short sales and normal sales can be seen in the following table.
| Median Values | Short Sale | Normal |
|---|---|---|
| Avg Mkt Time | 99 | 29 |
| Sales / List Price | 99.8% | 98.6% |
| Sales / Old List Price | 87.4% | 92.9% |
The most significant observation is that normal sales now tend to be pretty well-priced out the gate and are being purchased in less than 1/3 the time of a short sale. Of course, the time difference could merely be the delay in waiting on the lenders. Not surprisingly then, the sales price in a normal sale ends up being much closer to the asking price.
In conclusion... there are good buys out there and they are going quick. However, there are a ton of new listings that are still over-priced. So, look at the time on the market and check to see whether or not the price has already been reduced. Keep the above statistics in mind when making your offer.
Monday, March 10, 2008
What the New Jumbo-Conforming Loan Guidelines Mean to San Diego
A 9-page document describes the new lending guidelines (in response to the Economic Stimulus Act of 2008). So, let's cut to the chase(with minor over-simplifications for brevity).
$697,500 is the FHA limit for "jumbo-conforming" loans for San Diego. It should be the same for FNMA & FDMC.
Loan-to-value (LTV) requirements:
- 90% LTV for fixed-rate
- 80% LTV for adjustable-rate
- 75% LTV on a refinance; NO consolidation of 1st and 2nd; NO cash out*
No 30-day lates in past 12-months (on any housing debt)
ARMs must qualify at their reset rate
Full documentation is required
Borrowers must personally have 5% skin in the game
My view is that the lending guidelines are sound and I wish they had been in place four-years ago.
$697,500 is the FHA limit for "jumbo-conforming" loans for San Diego. It should be the same for FNMA & FDMC.
Loan-to-value (LTV) requirements:
- 90% LTV for fixed-rate
- 80% LTV for adjustable-rate
- 75% LTV on a refinance; NO consolidation of 1st and 2nd; NO cash out*
No 30-day lates in past 12-months (on any housing debt)
ARMs must qualify at their reset rate
Full documentation is required
Borrowers must personally have 5% skin in the game
My view is that the lending guidelines are sound and I wish they had been in place four-years ago.
Wednesday, March 5, 2008
Anne-marie Boyer interviewed on KUSI News
Real Estate Economic Stimulus
KUSI News, Inside San Diego, February 19, 2008
Click for Video
Lena Lewis and Bridget Naso interview Anne-marie about the effects of the Economic Stimulus Package on the San Diego Real Estate Market. More detail on this topic is provided at San Diego's Finest Real Estate blog - Real Estate Economic Aid.
Anne-marie says, "With interest rates at their lowest in four years, it is a great time for homeowners to refinance to convert a jumbo loan to a cheaper conforming loan, combine a first and second into a cheaper conforming loan, trade in a variable rate mortgage for a long-term fixed rate mortgage, reduce interest rates, or to just consolidate debt to reduce payments. "
Update: Due to recent dither within HUD, lenders have temporarily increased interest rates. We expect rates to come down again as soon as things firm up. (It is uncertainty, such as nearing an election, that cause worry and concern which in turn cause a temporary increase in rates.)
Transparency and New Conforming Loan Limits
HUD had 30 days from the date the law was passed, February 13th, to designate the median home prices and otherwise resolve all the ambiguity. However, the rumor mill indicates they may not get their act together until this summer. Additionally, there is currently discussion about not actually changing the conforming loan limit (per se), but rather "adding" a new loan classification - maybe they will call it conforming-jumbo.
All in all, that might be along the right lines, just not enough. The huge ripple effect through the financial community was partially driven by a lack of transparency - the claims that no one really knew what kinds of loans were in a portfolio. The argument is that if more were truly known about the loans, they could have been better rated for risk and priced accordingly. But, what can create the required transparency?
I have two recommendations. Context & Labelling.
Context (weighed heavily in my PhD research). Consider that a number without units (context) is worthless. What is my speed? 5. 5 what? Feet / second? Miles / hour? Although equity in a home is considered when the loan is first given, it seems to be an unknown when a loan is sold (re-sold) into the secondary market. After all, if people are getting 100% financing via a 1st-mortgage for 80% and a 2nd-mortgage for 20% (to avoid paying mortgage insurance) then there is no equity in the property. That is a very different 1st-mortgage than the one where someone has put down 20%.
Labelling. Label the loans by the key attributes. (This is really just a derivative of context when you look closely). Start with Loan Amount by Credit Score, in units of, say, $50,000 and 50 pts respectively. (E.g., Loan $250-300K & 500-550 FICO vs $550-600K & 750-800 FICO.) Such classification would provide the much needed transparency. Then, it is fairly easy for the market to "buy" a bucket of loans and to know exactly what they are getting. And the invisible hand of the market can efficiently price such loans. Better yet, loans that the market doesn't like will dissappear entirely for lenders who resell their loans or else will be priced higher (e.g., hard-money loans).
We must realize there already is (an N-dimensional 'grid') classification for loans based on #years, interest rate, payment schedule, interest only, etc. So all I'm really offering is that we add more attributes (context). In fact, as a programmer, I believe everything but the equity in the home is already available.
Of course, the more attributes to be measured and the increase in the number of divisions in each attribute result in a rapidly growing quantity of unique labels. E.g., 12 (credit score buckets) x 20 (price divisions) x 10 (equity divisions - say, by 10% percent) x 10 (loan term options) x NNNN = 24,000 x NNNN. Seems like a lot, but we seem to be able to have 'zillions' of different mutual funds. And besides, it is just a database and the numbers identified are quite small for our computers.
Now for the fun... (Another part of my research and work history is about information in real time.) What we will then need is to dynamically re-classify loans based on changes in equity. E.g., a $100,000 home equity loan removes that much equity out of the house, reducing the equity, say from a 25% down-payment to 5% remaining equity. This just made that first loan quite a bit more risky. This would take effort to implement and track, but it would stabilize the overall system by creating (and managing) the much needed transparency.
All in all, that might be along the right lines, just not enough. The huge ripple effect through the financial community was partially driven by a lack of transparency - the claims that no one really knew what kinds of loans were in a portfolio. The argument is that if more were truly known about the loans, they could have been better rated for risk and priced accordingly. But, what can create the required transparency?
I have two recommendations. Context & Labelling.
Context (weighed heavily in my PhD research). Consider that a number without units (context) is worthless. What is my speed? 5. 5 what? Feet / second? Miles / hour? Although equity in a home is considered when the loan is first given, it seems to be an unknown when a loan is sold (re-sold) into the secondary market. After all, if people are getting 100% financing via a 1st-mortgage for 80% and a 2nd-mortgage for 20% (to avoid paying mortgage insurance) then there is no equity in the property. That is a very different 1st-mortgage than the one where someone has put down 20%.
Labelling. Label the loans by the key attributes. (This is really just a derivative of context when you look closely). Start with Loan Amount by Credit Score, in units of, say, $50,000 and 50 pts respectively. (E.g., Loan $250-300K & 500-550 FICO vs $550-600K & 750-800 FICO.) Such classification would provide the much needed transparency. Then, it is fairly easy for the market to "buy" a bucket of loans and to know exactly what they are getting. And the invisible hand of the market can efficiently price such loans. Better yet, loans that the market doesn't like will dissappear entirely for lenders who resell their loans or else will be priced higher (e.g., hard-money loans).
We must realize there already is (an N-dimensional 'grid') classification for loans based on #years, interest rate, payment schedule, interest only, etc. So all I'm really offering is that we add more attributes (context). In fact, as a programmer, I believe everything but the equity in the home is already available.
Of course, the more attributes to be measured and the increase in the number of divisions in each attribute result in a rapidly growing quantity of unique labels. E.g., 12 (credit score buckets) x 20 (price divisions) x 10 (equity divisions - say, by 10% percent) x 10 (loan term options) x NNNN = 24,000 x NNNN. Seems like a lot, but we seem to be able to have 'zillions' of different mutual funds. And besides, it is just a database and the numbers identified are quite small for our computers.
Now for the fun... (Another part of my research and work history is about information in real time.) What we will then need is to dynamically re-classify loans based on changes in equity. E.g., a $100,000 home equity loan removes that much equity out of the house, reducing the equity, say from a 25% down-payment to 5% remaining equity. This just made that first loan quite a bit more risky. This would take effort to implement and track, but it would stabilize the overall system by creating (and managing) the much needed transparency.
Monday, February 25, 2008
Real Estate Economic Aid
$5,694 / year – every year, is to be given to homeowners nationwide by the economic stimulus package.*
$1B+ / year – every year, could be put back into the San Diego economy.**
* Homeowners who refinance loans in high-cost areas may save $5,694 per year due to the economic stimulus package. With the conforming loan limit being increased to as much as $729,750 in high-cost areas like San Diego, a number of homeowners may be able to trade in a jumbo loan or a first & second combination loan for a conforming loan. Because the interest rate on a jumbo loan is typically 1% higher than we find on a conforming loan, less mortgage interest will be paid. For example, on a $729,750 loan, reducing an interest rate of 6.75% down to 5.75% means a savings of $5,694 / year – every year!
** The National Association of Realtors indicates that 44% of transactions in San Diego fall below the current conforming loan limit of $417,000 and that 32% fall between the current limit and the new $729,750 limit. The US Census Bureau says that San Diego has 1,125,000+ housing units, of which 35% are multi-family. Hence, there are 731,250+ homes * 32% = 234,000 homes. At $5,000 apiece, we are well over $1B. You might be tempted to argue that a $5,000 average savings is high. It is. But, I believe the 32% might be low.
Why? Two reasons. First, we have first-hand evidence of a client refinancing their mortgage that is currently above the $729,750 loan limit. Now, that means a first and a second, but there is a significant savings to be had regardless. Second, 100% - 44% = 56%. So, we aren’t necessarily limited to 32%. If all 56% could save equally, then we’d be looking at $2B+ / year. Of course, not everyone can; some have no equity; others have loans that are just too large; banks are freezing some rates; and still others have awesome rates that they should just leave alone. And not everyone who can, will. Hence, “could” and “$1B”.
But the interesting thing about this is the comparison to the much-hyped “give something to everyone – except the rich” provision. The $600 / adult and $300 / child provision amounts to about $1.5B for San Diego. But is a one-time-only deal. The mortgage interest savings is every year until the loan gets replaced.
However, this provision expires at the end of 2008. My wife, Anne-marie, the mortgage broker, says, “It is important for people to act quickly … with hundreds of thousands of people looking to refinance, the system will become overloaded, there are only so many appraisers” She cites the last refinance boom where lenders artificially inflated interest rates to limit the flow of loans. She says people from anywhere in California with good credit may refinance with her at San Diego's Finest Real Estate for Loans aka www.SanDiegosFinestRealEstate.com. The phones are usually busy, but she can be reached 24/7 at aboyer@SDFRealEstate.com.
If we can put $1B+ back into the local economy, recurring annually, wouldn’t it be “un-American” not to refinance?! :)
$1B+ / year – every year, could be put back into the San Diego economy.**
* Homeowners who refinance loans in high-cost areas may save $5,694 per year due to the economic stimulus package. With the conforming loan limit being increased to as much as $729,750 in high-cost areas like San Diego, a number of homeowners may be able to trade in a jumbo loan or a first & second combination loan for a conforming loan. Because the interest rate on a jumbo loan is typically 1% higher than we find on a conforming loan, less mortgage interest will be paid. For example, on a $729,750 loan, reducing an interest rate of 6.75% down to 5.75% means a savings of $5,694 / year – every year!
** The National Association of Realtors indicates that 44% of transactions in San Diego fall below the current conforming loan limit of $417,000 and that 32% fall between the current limit and the new $729,750 limit. The US Census Bureau says that San Diego has 1,125,000+ housing units, of which 35% are multi-family. Hence, there are 731,250+ homes * 32% = 234,000 homes. At $5,000 apiece, we are well over $1B. You might be tempted to argue that a $5,000 average savings is high. It is. But, I believe the 32% might be low.
Why? Two reasons. First, we have first-hand evidence of a client refinancing their mortgage that is currently above the $729,750 loan limit. Now, that means a first and a second, but there is a significant savings to be had regardless. Second, 100% - 44% = 56%. So, we aren’t necessarily limited to 32%. If all 56% could save equally, then we’d be looking at $2B+ / year. Of course, not everyone can; some have no equity; others have loans that are just too large; banks are freezing some rates; and still others have awesome rates that they should just leave alone. And not everyone who can, will. Hence, “could” and “$1B”.
But the interesting thing about this is the comparison to the much-hyped “give something to everyone – except the rich” provision. The $600 / adult and $300 / child provision amounts to about $1.5B for San Diego. But is a one-time-only deal. The mortgage interest savings is every year until the loan gets replaced.
However, this provision expires at the end of 2008. My wife, Anne-marie, the mortgage broker, says, “It is important for people to act quickly … with hundreds of thousands of people looking to refinance, the system will become overloaded, there are only so many appraisers” She cites the last refinance boom where lenders artificially inflated interest rates to limit the flow of loans. She says people from anywhere in California with good credit may refinance with her at San Diego's Finest Real Estate for Loans aka www.SanDiegosFinestRealEstate.com. The phones are usually busy, but she can be reached 24/7 at aboyer@SDFRealEstate.com.
If we can put $1B+ back into the local economy, recurring annually, wouldn’t it be “un-American” not to refinance?! :)
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