Valuation Matters

Case-Shiller Index Is More Than A Monthly Housing Number

2011-12-12T11:41:00.024-05:00

The Case-Shiller index has gained acceptance and popularity to the point that its monthly release is one of the most watched, followed and talked about among all of the periodic economic releases. Needless to say, it makes the job of researchers much simpler in that they do not need to reinvent the wheel every so often with competing, if not conflicting, statistics. Additionally, it has helped create a multi-billion dollar derivatives market where sophisticated investors now routinely hedge their real estate and mortgage portfolios. For example, residential REITs now have access to a market mechanism to protect themselves against a declining market. However, to most who follow the Case-Shiller index closely it is just a monthly number informing one whether the current prices are heading higher or lower.

This piece will, on the other hand, demonstrate to and enlighten its readers of the entire universe of the Case-Shiller indices and lead-up data – from the basic Composite-10 and 20 Indices (“Major”) to Major Market Condo Indices to Tiered Home Prices to National Quarterly Indices to Sales Pair volumes underlying the monthly analyses, etc.

(Click on the image to get an enhanced view)

The Major-10 and 20 Indices track the major markets, keeping its followers abreast of the month-over-month price changes and, in turn, the overall directions. Considering this index is computed off the arms length repeat sales, it is far superior to the median house prices that are published monthly by various government agencies and trade organizations. The above index chart demonstrates that the prices declined 31% between 2006 – the peak – and 2010 and this trend has been continuing unabated in 2011, thereby forcing the current prices down to the 2002-03 levels. Due to the tightened lending standards the sales pair counts have also plummeted over 55%. Considering that the fundamentals of the housing market are unconvincingly fragile, it is too premature to talk about any recovery or even consolidations in the near future. It may take easily 2 to 3 more years to get the excess inventory – pre-owned as well as new – absorbed. Of course, even within these composites, certain markets performed significantly better than the others. Since all real estate investments are uniquely local, investors must use the local index rather than the national composites to make prudent investment decisions.

Since the condo market often works as the leading indicator of the housing market – both on the way up as well as the way down – having access to the separate Condo Indices is extremely useful for those especially interested in that particular housing segment. Of course, Condo Indices are currently available for only five major markets. Given its growing importance among analysts and investors, its coverage is expected to be expanded to the other major markets – in line with the housing markets – as well. The above graphics clearly show that the North-East condo markets have held up remarkably well compared to their counterparts. The prices of the New York and Boston markets have retreated only 11% and 13% from the peaks of the recent housing frenzy as opposed to 29%, 35% and 40% for Chicago, San Francisco and Los Angeles, respectively, although Los Angeles produced a whopping 156% return between 2000 and 2006 beating even New York which includes the ever-resilient Manhattan market, one of the most sought-after condo markets by the global investors. The fact that New York market retreated only 11% from its highs speaks volumes of the metallurgy of the Manhattan market, without which the index could be significantly lower.

The National Quarterly Indices are very useful for analysts building national-level forecasting models for the housing market. Considering that the quarterly indices are inherently more liquid -- meaning, it is backed by more sales -- than the monthly indices, the quantitative models built off the quarterly indices are more stable and effective. If you happen to be in that particular field, please use this index to build the challenger models as compared to the monthly housing indices contributing to the construction of the champion models. In line with the major monthly housing indices the National Quarterly Index also fell 31% between 2006-Q1 and 2009-Q1, following which the market was artificially propped up until 2010-Q2 by a series of government interventions including two homebuyer tax credits which expired in April, 2010. Since then, as the chart demonstrates, the market resumed its steady downward spiral, eroding all of the gains made during that intervention period.

Finally, I must say, my favorite is their monthly Tiered Price Analyses, broken down by the markets. As we all know, the different price tiers of the market – lower tier, mid tier and upper tier – do not necessarily move in tandem so it is crucial to analyze them separately. While the “one size fits all” indices capture the body of the bell curve, they do not efficiently portray the movement of prices in both ends of the curve. Therefore, those who target a particular price tier should significantly benefit from their monthly tiered prices. Additionally, the AVM modelers should always use tiered prices – as opposed to median/overall prices – to make adjustments to their raw sale prices (FYI - Time adjusted sale price becomes the dependent variable in multiple regression-based AVMs) to make their models truly efficient. Case in point: In this Atlanta example, if the sale prices were adjusted using the overall prices instead of the tiered prices, the low and mid tier adjustments would be terribly flawed, although the final quality model metrics like COD, PRD, etc. would appear just fine considering that the final sales ratios – the primary yardstick of the model effectiveness – would be computed off the time adjusted sale prices relative to the predicted prices, thus masking the inherent inefficiency of the model.

Anyone needing more detailed analysis of any of these indices and methods as well as how the investors could use them in their investment decision-making should read my book “How to Predict US Housing Markets with Case-Shiller Indices.” Note: This book is FREE until 01-31-2012.

Links to my related books (No Kindle is required):
http://www.smashwords.com/books/view/79216
http://www.smashwords.com/books/view/84236
http://www.smashwords.com/books/view/84216

Also, check out my interview in Mortgage Banking (December, 2011), outlining the challenges the AVM industry currently confronts.

Thanks,

Sid Som
sidsom1@yahoo.com

Data Source:
Published as of 11-29-2011
http://www.standardandpoors.com/indices/sp-case-shiller-home-price-indices/en/us/?indexId=spusa-cashpidff--p-us----

Homequant.com Announces Release 2.0 with Interactive Google Maps

2011-11-11T08:44:00.005-05:00

PRESS RELEASE

New York, NY, November 11, 2011 --(PR.com)-- Homequant.com is announcing the launch of a vastly improved product with end-to-end integration of Google Maps.

Homequant.com is the art and science of valuing a single family residence (“SFR”) on the net. Instead of offering old frozen values, Homequant.com is designed to empower its users with an innovative way to value a residential property.

With the integration of Google Maps, now users can value a SFR at two different levels – at the property level as well as at the neighborhood level. To value at the property level, all one needs to know is the property address, the name of the neighborhood and the approximate size and age of the subject property. Homequant.com then helps match the recent comparable sales and produces a valuation report that looks more like a professional comparable sales analysis report, including a complete analysis of the value parameters. Alternatively, if the property address is unknown, the subject could still be valued at the default neighborhood level.

And everything is in plain English, presented in an easy-to-understand format, without the usual appraisal jargon. And, it’s all free and requires no registration or login whatsoever.

Homequant.com is not only an excellent market analysis tool for current and future homeowners, but it is also great for analysts, appraisers, assessors, brokers, salespeople, hearing officers and mortgage professionals needing sample values on-the-go or quick validation of paid AVM or BPO values, without having to use a complicated professional valuation system or a proprietary listing service.

Additionally, the macro ‘Sales Query’ module will help visitors understand the econometrics of the broader markets, starting at the neighborhood level.

Homequant.com is developed by an industry expert with 20+ years of expertise in appraisal research and automated valuation modeling.

###

If you’d like more information about this website, or to schedule an interview with its developers, please call 718-314-4081 or email: contact@homequant.com.

_____________________________________________________________

NOTE TO INVESTORS

The management of Homequant is planning to dilute up to 20% of equity shares to investors to raise additional capital to expand into all major US/Canada markets, as well as introduce a subscription-based professional version in 2012. Interested parties are asked to send email queries to sidsom1@yahoo.com.

Bailing Out The Dysfunctional Civil Service System

2011-10-25T15:02:00.007-04:00

** NO KINDLE IS NEEDED -MULTIPLE TRADITIONAL FORMATS INCLUDING PDF- ARE SUPPORTED **

** CLICK ON THE TITLE ABOVE OR THE LINK BELOW TO PREVIEW / ORDER **

http://www.smashwords.com/books/view/78686

Bailing Out The Disfunctional Property Tax System

2011-10-25T14:48:00.008-04:00

** NO KINDLE IS NEEDED -MULTIPLE TRADITIONAL FORMATS INCLUDING PDF- ARE SUPPORTED **

** CLICK ON THE TITLE ABOVE OR THE LINK BELOW TO PREVIEW / ORDER **

http://www.smashwords.com/books/view/78916

The property assessment and tax system in the US is totally antiquated and dysfunctional. This book will reveal how this dysfunctional system can be brought back to life, and how the displaced assessing and valuation personnel can be redeployed without having to switch to another industry.

AVM Book - How To Build A Better Automated Valuation Model (AVM)

2011-10-13T20:31:00.010-04:00

** NO KINDLE IS REQUIRED **
** MULTIPLE FORMATS - INCLUDING PDF - ARE SUPPORTED **
** PLEASE CLICK ON THE TITLE ABOVE TO PREVIEW AND ORDER THE ACTUAL BOOK **

Reader testimonial
"One of the best books I have read on Valuation modeling techniques. I recommended it for both the novice users to those more intermediate to advance.

My favorite chapters are “The 10 Steps to Build an Effective Automated Valuation Model” and the section on residuals analysis.

Also, noteworthy is the second book that has a chapter on how to build a quick MRA model using Excel.

Great books at a great price!"

This book will teach you the issues and techniques that are rarely found in textbooks and courses offered by professional institutions. It covers such hands-on chapters as statistically significant sales sampling, broader market time adjustments, categorical modeling, multicollinearity, residual analyses, systematic removal of outliers, proper model testing, etc. to help build a better and more advanced AVM.

AVM Book - Alternate Applications of Automated Valuation Models (AVM)

2011-10-13T20:25:00.010-04:00

** NO KINDLE IS REQUIRED **
** MULTIPLE FORMATS - INCLUDING PDF - ARE SUPPORTED **
** PLEASE CLICK ON THE TITLE ABOVE TO PREVIEW AND ORDER THE ACTUAL BOOK **

This book will teach you the wide-ranging alternate applications of AVMs outside of residential modeling – from the universe of commercial modeling to REO and foreclosure modeling to MLS-based data modeling to stress testing mortgage or assessment portfolios using challenger AVMs, etc. Also included are much sought-after topics like Excel-based modeling, forward sales sampling to minimize sales chasing, and the proper process to evaluate a vendor or vet a consultant.

Franchise Feasibility of Property Tax Appeals

2011-09-06T09:53:00.005-04:00

Since property valuation is not an exact science – even with the explosion of AVM’s – tax appeals are common everywhere. However, the volume of appeals varies wildly from place to place. On the heels of the dire straits most taxing jurisdictions are in, cyclical assessing will rapidly take root and soon become universal. In fact, the green shoots are already popping up all around. Although cyclical assessing (one appeal allowable per cycle) is expected to reduce the traditional appeals volume significantly, appeals from the cyclical process would nonetheless be reinvented because of the obvious asymmetry in market conditions within and between cycles. As is well known, the housing market has become extremely volatile and that volatility is here to stay, causing and adding more to the cyclical asymmetry.

Despite what the assessors say, annual reassessments are traditionally grossly flawed for three fundamental reasons:

a) Assessment is generally a futuristic gamble stemming from the futuristic valuation dates, making assessment rolls anywhere from inaccurate to highly inaccurate (read my prior piece ‘Should Taxable Status Date be Forward or Backward?’ for details).

b) Most mass appraisal models are general linear models or are predicated on a set of linear assumptions, thereby producing vastly distorted values on both ends of the size curve (below the 25th and above the 75th percentile – thus 50% of the values are generally questionable).

c) Sales time adjustments are generally median-based, disregarding the broader markets and thus invoking irrational time corrections, which, in turn, destabilize valuation models and produce inconsistent values (read my prior piece ‘Why Broader Markets Need Evaluated for Time Adjustments in AVM’).

Now that the assessing industry is quickly moving to the cyclical assessing, the market asymmetry within and between cycles will give rise to large volumes of new appeals atop the above-mentioned traditional appeals. Therefore, the overall appeals volume is expected to rise, rather than decline.

The Franchise Option

In fact, tax appeals processing can easily be developed into a very profitable franchise business. Once it becomes a proven formula in one area, it just has to be duplicated in other areas. Although the format for each county, even within the same state, would be slightly different in keeping with its assessment logistics and political apparatus, they would all share the same state laws and aid requirements, making it easy for the franchisor to have one general format per state (or, per province in Canada). From the franchisor’s point of view, as long as the underlying concept is rock solid and can be easily duplicated, potential franchisees will be enticed. From the franchisee’s point of view, considering it is a service franchise which is inherently more lifestyle-oriented, it must offer both economic viability as well as a favorable lifestyle opportunity. The small changes to the format would be moot as long as the formula develops into an established brand. Case in point: If McDonald’s is so enormously successful in India where most consumers are vegetarians, we can safely conclude it’s a brand backed by a proven formula.

If there are 3,000+ counties in the US and at least the top-1,000 layer is easily franchisable (and Canada is not drastically different either), just think about the possibilities. Each franchisee would get a protected territory – defined by Census Tracts and Census Blocks so neighborhoods are not shared – of roughly 100K single family residential (“SFR”) parcels, allowing 1 to 8 franchisees per county depending on the given liquidity. Out of the 100K SFR population, the franchisee would pursue roughly 49.8% or 50K risk cases, calculated as follows: -34.1% under the bell curve (that is, -1 SD) would constitute the Mid-risk group, while -15.7% under the curve (that is, additionally up to -3 SD) would make up the High-risk group. Since the risk AVM would be based off non-linear regression as opposed to generally linear tax roll values as well as the CMA values, allowance for any margin of error would be unnecessary in establishing the risk curve. Note – detailed explanations of these statistical considerations are available in the business plan for qualified venture capitalists.

The Franchise Nitty-gritties

During the introductory cycle (three years into the franchise) even if the effectiveness is a mere 15% - translating to only 7.5% market share – it will grow rapidly in the second and third cycle (six and nine years into the franchise) to at least 30% and 50% respectively, almost decimating the traditional competition and producing a fast expanding market share for the franchisees. Well-run franchises should eventually achieve at least 60% effectiveness of their respective markets. Since this would be knowledge-based service franchise, most eligible franchisees would come from related professional environments – current and former assessing personnel, appraisers, realtors, loan officers, hearing officers, real estate educators, real estate lawyers, AVM and CAMA analysts, tax mappers and, of course, the traditional appeals processors who would see the writing on the wall.

(click on the image to get an enhanced view)

Based on the above projection, while the breakeven would be reached by the end of the first cycle (3rd year into the franchise), franchisees would be making money in the second cycle, with rapid acceleration in the third cycle. The bone of contention here is the assumption of an average of $300 in tax savings. It could be considered high in annual reassessments, but in cyclical assessments where market disconnects within and between cycles are significantly higher, such savings could be more than reasonable and realistic. Likewise, 15% effectiveness or 7.5% market share could be easily achieved if the franchises are launched at least six months ahead of the start of appeals filing, allowing enough time for the TV and print ads to kick in and yield meaningful results. The projection also assumes outsourcing 35,000 cases leaving 15,000 (5,000 per year) lesser complicated cases for the partners to undertake. Since home-grown CMAs would be provided to the outsourcers, just $10 per case would suffice to provide the negotiation support which is generally done on a volume (4 to 6 cases per sitting hour). However, if three partners with direct industry knowledge join together to buy into a franchise, they could save most of the outsourcing costs, thus vastly improving their bottom-line from the very beginning. Nonetheless, all franchisees would be trained on CMA’s as well as the art of negotiation.

Unlike traditional mass filings, the marketing costs – costs of advertisements and mailers – would be significantly higher here to swiftly penetrate the market and gain market share. Similarly, the office overheads – rent, office help and technology – would also be higher to meet the franchise requirements; for example, the office location and space would be researched and leased by the franchisor and then sub-leased to the franchisee. On the other hand, the cost of CMA production, though an expensive proposition traditionally, would be virtually free here (except for the printing supplies) with the help of the franchisor’s proprietary batch processing CMA software.

Jurisdictions still practicing annual reassessments might initially appeal to the prospective franchisees as prime franchise territories with higher income potential, but as those jurisdictions gradually move to cyclical assessing any windfall possibility would be wiped out. Those that are in 4 to 6-year cycles would gradually revert to 3-year cycles (read my prior piece ‘Why Property Assessing Must Change to Keep Municipalities Afloat’) to get a better handle on the asymmetric market conditions between cycles, consequently enhancing financial opportunities for those franchisees.

Apart from the initial $20K in franchise fee, franchisees would need a liquid net worth of at least $150K for the initial fixed costs to ensure smooth sailing during the first two years when cash flows would be virtually absent. Additionally, to defray the cost of the initial outsourcing, $350K in short-term franchise financing would be needed. The high net worth requirement by the franchisors helps separate the serious from the curious, as well as protect the franchise branding process. In line with other successful service franchises, this franchisor would also take advantage of the cooperative TV and print (yellow page and banner) ads leveraging (local) franchisees’ marketing dollars to swiftly penetrate the market and establish the brand name. Also, full-time employees could be shared by franchisees to reduce dependence on the part-time and seasonal employees, promoting better knowledgebase, lower turnover and reduced training costs.

Advantages of Tax Appeals Franchising

1. The Proven Formula and the Format: This would consist of four essential ingredients – cutting edge automated valuation modeling (AVM) and desktop appraisals (CMA); sophisticated risk methodologies; advanced training in face-to-face negotiations, and forward-looking marketing techniques, in addition to the standard start-up and ongoing franchise supports.

2. Protected Franchise Territory: Each franchisee would get a protected territory of roughly 100K SFR parcels, defined by Census Tracts and Blocks. Thus, franchisees would never compete with one another; instead, they would work complimentarily in sharing marketing budgets, manpower, technology, leads and referrals, etc.

3. Risk-based Target Marketing: Under the traditional format mass filers target the entire jurisdiction with little to no knowledge of scientific risk analysis, thereby assigning the same level of risk for all risk groups. This franchise format will scientifically evaluate the level of risks for all parcels within the territory and then target only the high and mid-risk groups (roughly up to 50%) with clear and present economic viability, minimizing any wasteful targeting.

4. Cooperative Advertising and Promotion: To penetrate any market mass marketing is essential. Franchisees’ advertising budgets will be pooled (county to MSA level) to produce TV, print, and internet ads, achieving the maximum economy of scale. Franchisees will use the market-tested mailers from the franchisor’s catalog, saving a bundle in unnecessary market research and graphic design.

5. Rapid Capture of Market Share: Because of the inherent advantages of franchising consumers will quickly and easily recognize the emerging brand name, which will help franchisees gain market share from the traditional competitors at a rapid pace. As part of the marketing campaign, franchisees sharing the common markets (same appeals jurisdictions) will also jointly sponsor a series of seminars and outreach events every year where invitees can meet them face-to-face and address their concerns. Again, the risk analysis will help create the list of invitees.

6. Easy Access to Financing: Although most banks and financial institutions will not lend to start-up businesses, they do however treat new franchisees as existing businesses and lend on the reputation of the system itself. Most franchisors have special agreements with certain institutions. Also, there are lending institutions specializing in franchise financing.

7. Better Professional Service Franchise: Since the economy has become more service-oriented service franchises have been growing by leaps and bounds. However, professional service franchises (e.g., Nurse-finders*, Accountants on call*, etc.) are relatively few and far between, not considering real estate sales, of course. As the assessing, appraisal and realty businesses continue to contract, this appeals processing franchise will become extremely enticing to the industry evacuees.

8. High Net Worth Requirement: Franchises like to deal with financially qualified and committed parties only. Studies show at least 50% of all non-franchise start-up businesses fail, while that rate is as low as 5% for franchise businesses. The primary reason those non-franchise businesses fail is due to inadequate capital. Franchisors do not like to succumb to that problem. Moreover, a franchise is like a brotherhood in which the members all help each other. Even if a single franchisee goes down, it has a very negative impact on the entire system.

9. Constant Research and Innovation: Since the franchisors only make money when the franchisees make money (for example, ongoing royalty, future franchise developments, etc.), they are always at the forefront of research and innovations to stay ahead of the competition. However, unlike non-franchise businesses, franchisees do not have to spend any time working on research and innovations to continually stay ahead of the competition. They just need to concentrate on maximizing returns from only their territories by rigorously following the franchise format.

Being The Franchisor

Finally, let’s do the numbers for the franchisor. By the end of the sixth year the franchisor should have at least one hundred active territories under the corporate belt, grossing $5.6M annually – $56K average annual royalty per franchisee during first and second cycle – even discounting the other revenue sources like the $20K initial franchise fee per development and AVM fees that would be done by the same team (the team expands as the franchise grows so it is a semi-fixed cost). Actually, the number of franchises could far exceed one hundred considering the income potential from this revolutionary service franchise vis-à-vis other competing service franchises like maid services, janitorial services, carpet cleaning, property inspections, computer repairs, hair salons, math schools, temporary help, etc. The franchisor would need a start-up capital of at least $300K – $150K payable to a recognized franchise development corporation plus $150K in marketing.

After the initial gestation of six years, the rapid growth in brand recognition, rising unemployment among those aged 50+, the steadfast decline in the assessing universe and appraisal business etc. would contribute to an exponential growth in franchisor’s US business, mightily shoring up the balance sheet. The huge cash build-up would lead to other opportunities like acquisition of a national data warehouse, expansion into Canada and venturing out in commercial properties, to list a few possibilities. As soon as the franchise hits the magic “Inc. 500” list, the true IPO potential emerges.

Thanks,

Sid Som MBA, MIM
Suraj Som BA (Harvard)
sidsom1@yahoo.com

Note – 2011 Copyrighted content (US Copyright Reg. No. TXu 1-752-612)

Considering the scope of this project, we will explore any meaningful Joint Venture participation. Open to other possibilities as well.

Try Hedged Sector EFTs to Minimize Portfolio Risks

2011-09-02T10:45:00.011-04:00

This is an excerpt from a Chapter from my new book "How to Protect Stock Portfolios from Violent Market Swings."

** Please click on the title above to preview the book. **

Exchange trade funds (ETF) have been around for over a decade now and the fact that there are over 1,500 of them on American exchanges speaks to their rapidly increasing popularity. They have emerged as excellent investment vehicles for those who might not have the time for research and the stomach for the volatility of individual stocks, yet would enjoy self-directing their portfolios without having to succumb to the idiosyncrasies of the traditional mutual funds.

In fact, in an effort to emphasize reduced risks from the wild market swings as well as the potential savings ETFs offer (relative to the competing mutual funds in terms of the latter’s generally higher expense ratios and often hefty front or back-loaded sales commissions) and ease of entry and exit from the trade, independent financial planners have increasingly been recommending ETFs to their clients over individual stocks.

This chapter focuses strictly on the nine sector ETFs – known as SPDRs (Standard and Poor’s Depository Receipts) – that track the S&P 500, the most well-known index of the broader stock market. The nine sector ETFs are: XLB (Material), XLE (Energy), XLF (Financial), XLK (Technology), XLI (Industrial), XLP (Consumer Staples), XLU (Utility), XLV (Healthcare), and XLY (Consumer Discretionary). Again, those who would like to self-direct their portfolios without having to depend on individual stocks or mutual funds should seriously consider these sector ETFs – in addition to other asset classes like bonds, precious metals, managed futures, etc. – for their portfolio.

Since sector ETFs are well diversified, comprised of 30 (XLB) to 81 (XLF) stocks each, they provide the necessary protection from the potential fallout of individual stock. When unexpected bad news hits a certain stock, it can be clobbered for a while. Worse yet, it confuses investors as to whether that news could have a long-term impact, often preventing them from averaging down on the stock. Conversely, it would be only one out of the 30 to 81 stocks in that ETF. Investors would always know the real-time holdings of each ETF. Sector mutual funds are also equally diversified, but the money managers do not disclose their entire holdings live, keeping investors uninformed until the fund’s statutory reporting.

The above ETF table shows the financial sector has been significantly under-performing relative to its peers. While the median YTD return is 6.50%, XLF’s return is -6.68%. I am not going to get bogged down as to the reasons for this under-performance; instead, I am going to explore this sector as a potential investment opportunity going forward. The ‘Volatility’ is created off the spread of the 52-week high and low prices – therefore, the wider the spread, the higher the volatility the sector poses. In addition to the YTD return and volatility, the other metrics to consider are: liquidity (Volume - 3-month average volume), price earnings ratio (PE) and dividend yield (Div Yld). The liquidity is important to avoid having to deal with a potentially crowded exit door, while PE and Div Yld are also important quality measures showing if the exploratory ETF is totally out of sync and thus is too risky to invest in.

No doubt, XLF has a depressed YTD return and the second highest volatility; it is nonetheless most liquid with reasonable PE and Div Yld. The standard bottom-up stock research requiring thorough balance sheet analysis, tracking insider activity (buying and selling) and stock repurchases, etc., are not needed in ETF research. ETF research requires two elements – peers and hedge. I strongly believe the naked entry into an individual stock or an ETF, whatever potential it may offer, without accompanying and true hedges (explained later) is a gamble, not an investment.

To many, for the stock market to be healthy, the financial sector has to provide the leadership so the depressed return here is strictly a short-term market event. As the financials gradually regain leadership, this ETF – to them – should outperform the other sectors. Since my objective here is to describe and emphasize the methodology I am proposing, let me agree with them and proceed, pivoting XLF alongside its top six holdings.

XLF with a basket of 81 stocks from the different sub-sectors – banks, brokerages, insurers, mutual funds, REITs, rating agencies, etc. – closely parallel even the best performing stocks in the sector. In fact, it has a low volatility too, next only to American Express (AXP). Then again, considering this is an ETF, it does not have the usual headaches of the individual stocks. For example, as of this writing, Bank of America (BAC), undoubtedly a great American institution, is getting hammered and its stock prices lately hit a new 52-week low due to a string of lawsuits from other banks. No denial, the falling BAC prices would also impact XLF investors to some extent, but nowhere close to what the over-weighted stockholders would be. While the elevated volatility is generally good for day trading, it could be stomach-wrenching for the investors, particularly for those who bought close to the 52-week high and are now unable to average down. Furthermore, they would be constantly fearful that more bad news might be in store. In hindsight, XLE could have been a great vehicle for them.

As I indicated before, the methodology I am proposing here is not just naked ETFs replacing individual stocks, but must also be coupled with a hedge to have an alternating protection. In fact, investors who would prefer stocks by devoting the time to research and willing to ride out the volatility, should also seriously consider the hedge I am ready to talk about. Here is how to identify the hedge.

Please consider the book to continue reading this piece…

If You Need Commercial AVM Services!

2011-09-01T15:59:00.004-04:00

(please click on the image to get an enhanced view)

** Please click on the title 'If You Need Commercial AVM Services' above to preview the book on AVM **

Don’t be Fooled by High Dividend Yields Only – Learn to Use Dividend-EPS as the True Metric

2011-08-23T10:51:00.009-04:00

Here is an excerpt from a chapter from my new book "How to Protect Stock Portfolios from Violent Market Swings." Click on the title above to preview it.

Investors’ love affair with high dividend paying stocks is well-known, generally occupying a special place in their asset allocation models, particularly for the senior people who tend to be more conservative. Therefore, the dividend paying stocks comprise a much bigger slice of the allocation pie for the senior rather than for the younger investors with more aggressive growth appetite and tolerance. Considering most of those stocks are also the bellwether companies, they are inherently more attractive in the marketplace. The high dividend components of the Dow Jones Industrial Average (“Dow-30”) are therefore the most sought-after from the dividend point of view.

One of the most popular dividend investment strategies is the “Dogs of Dow” popularized in the early ‘90s by Michael O'Higgins. This strategy calls for reinvestment in the ten highest dividend-yielding (dividend divided by stock price) Dow-30 stocks annually to maximize income while minimizing portfolio volatility as these companies usually weather the cycle storms more effectively than their counterparts. Since this is a short-term dividend strategy requiring annual readjustment in line with the new top-10, it does not help create long-term dividend portfolios. In fact, in the following analysis I will demonstrate that the highest dividend yielding stocks are not necessarily the best dividend stocks if a longer-term – three to five years – perspective is the objective of the portfolio.

The proper way to choose the high dividend stocks is to analyze them alongside their earnings per share (EPS). When the dividend yield is the lone determinant – as is the case in the “dogs” strategy – mutually exclusive of the earnings, the true underlying picture is obviously missing. The dividend earnings ratio – dividend per share (DIV) divided by EPS – is therefore the real determinant which creates a better selection platform by connecting the dividends to the earnings they are derived from. For example, when two competing stocks (that is, from the same sector) have very similar dividend yields but one shows a significantly higher DIV-EPS than the other, the latter is a better dividend stock than the former as it is strengthening the company’s cash position while paying out a sizable dividend.

The Dow-30 table (cut short here) shows the dividend yield (DIV YLD) and dividend earnings ratio (DIV EPS) side by side to make a compelling case as to why the latter is a more important metric. Let’s consider the three stocks from the same sector – Merck, Pfizer and Johnson and Johnson (J & J) – as the comparison must be “apples-to-apples.” Since Merck and Pfizer have much higher dividend yields than J & J’s (over 100 basis points), most stockbrokers and financial planners would obviously suggest Merck and Pfizer ahead of J & J to their clients. Now, if you bring earnings into the picture...

Check out the book (click on the title above) for the rest of the chapter...

How to Use Various High-Low Ratios to Define Entry-Exit Points in Equity Markets

2011-08-17T16:36:00.014-04:00

This is an excerpt from a chapter from my new Book "How to Protect Stock Portfolios from Violent Market Swings."

** Please click on the title above to preview the actual book **

Sophisticated short-term investors and traders use different methods, metrics, and indicators to decide when to enter or exit from the market. While a small subset - generally consisting primarily of specialized hedge fund managers - plays both sides of the market by using (and adjusting) their market neutral, long-short strategies, etc. rarely leave the market, most tend to play only the long side of the market by perfecting their methodologies. Whether they play both sides or only the long side of the market, they all know precision is the name of the game considering equity markets over the years have become extremely volatile. A few wrong trades can easily do irreparable damage to their portfolios, often inflicting 20% to 30% loss. Since most traders use margin money, this level of losses could easily devastate some. These investors and traders therefore continually fine-tune and market-adjust their models to ensure accurate and consistent prediction of their entry and exit points – generally via some pre-set limit and stop triggers.

In this chapter I am going to demonstrate how to use the various ‘High-to-Low’ ratios to decide on the entry and exit points. Obviously, the monthly closing data are more liquid than the weekly closings so I have used the monthly data. Of course, as I have repeatedly indicated and emphasized in my other books, no methodology is ever reliable and usable unless it is alternatively validated on an ongoing basis. Therefore, users should also use the weekly closing data to challenge and validate the champion monthly data. Since the market volatility often dramatically changes in the short-run on unexpected news and events (case in point: on the heels of the recent US credit downgrade by S&P, tsunami in Japan, etc., the market made dramatic moves on both sides), rolling weekly validations could help temporarily adjust the monthly triggers until the effects of that unexpected event, so to say, dies down. The most recent 6 months (26 weeks) of data would suffice to develop the challenging metrics.

The data series in this study consists of the last 24 months of data, although the Aug-2011 is partial. While the sigma is traditionally computed off mean, I have used median to compute the sigma here in order to get a more stable metric. In the olden days when these statistical measures were invented, mean used to serve as the basic measure of central tendency. Today, most market practitioners like myself tend to use the median as it reduces the influence of the outlier data points. If you prefer to stick to the textbooks, please go ahead and use the mean instead – the methodology I am proposing here will still be equally statistically significant. In the following examples, one sigma therefore means one standard deviation (+/-) around the median. If you are not up-to-date as to the use of the modern statistical measures and metrics, please consult my book entitled “How to Predict US Housing Markets with Case-Shiller Indices.”

The two ratios ‘High to Low’ and ‘Open to Close’ are the two ratios that help create the ‘1 Sigma’ decision metrics. The correlation between these ratios is moderate (0.452222465), meaning that they do not necessarily move in tandem. However, when they move up in lockstep frantically exceeding the upper limits of their respective ‘1 Sigma’ ranges, the market trends quickly...

Please preview the book to continue reading...

How to Predict US Housing Markets with Case-Shiller Indices

2011-08-05T18:31:00.013-04:00

** NO KINDLE IS REQUIRED NOW **
** MULTIPLE FORMATS - INCLUDING PDF - ARE SUPPORTED **

To preview/download the actual book please click on the title above.

This book reveals how to use the powerful Case-Shiller indices to analyze, model and predict the future trends of the US Housing markets. It covers the indices end to end - from the Major Market Indices to Condo Indices to Quarterly National Indices to Tiered Prices to Paired Sales, and many more, with nearly 50 graphic illustrations.

How Investors Can Use Case-Shiller Index

2011-07-03T22:44:00.018-04:00

Dear Readers,

This piece has been replaced by a separate chapter with updated data and analysis in my new book "How to Predict US Housing Market with Case-Shiller Indices." To learn the wide variety of economic implications and uses of the Case-Shiller Indices, please read the book. To preview the book, please click on the title page above.

How to Search for an Outsourcing Partner Overseas

2011-06-28T23:53:00.005-04:00

The recent Great Recession has squeezed credit and consumer spending out of the system to a point that many small businesses in the US now survive by the month. More unfortunately, the businesses that used to depend largely on the annual contracts from states and local governments are by and large on life support. While cutting costs during downturns is a necessary survival condition, an un-optimized and irrational approach to cost cutting may often be more counter-productive, if not disastrous. In fact, the better approach to cost cutting is cost improvement, which helps lower costs while improving productivity, or at least holding the line on the existing productivity.

In today’s technological world one obvious area in which most small businesses could achieve such cost improvement is the area of technology itself. The cost of technological development in the US is significantly higher – often six to tenfold – than in some of the emerging countries like India, China, Malaysia, Sri Lanka, Philippines, Thailand, Indonesia, Mexico, Poland, Bulgaria, etc. Those who have ongoing technology/development needs should seriously consider locating a good outsourcing partner in one of those – and many such (Google the list) – countries. I am not talking about the application/software developments firms only; such outsourcing partnership can immensely help other small businesses – from consulting to professional services to retail to industrial to real estate to education, etc. – not only to live through the current downturn but will help develop a competitive global mindset, thus strengthening the composition of the overall foundation. The difference could be more than just survival vs. collapse, perhaps growth vs. collapse by rapidly narrowing the ailing competition down.

Of course, locating the right outsourcing partner overseas is not an easy task; it requires a significant amount of research and planning. Having spent much time over the last several years researching and dealing with outsourcing partners, I thought I would share my experience with my fellow small business owners here to entice them to explore similar opportunities. Again, explore this avenue if your business happens to significantly depend on keeping pace with technological innovations and support. Alternatively, if your business needs no more than a plain vanilla web application with limited e-commerce, don’t waste time on it as the possibility of any meaningful cost improvement is virtually non-existent. By now, my regular audience knows I am an atypical thinker, often offering insights that are not generally available in text books, newsletters or blogs. Let’s test a series of scenarios (I do not have empirical data to test null hypotheses):

1. My friend recently moved back to set up an outsourcing shop in his home country which is emerging as a booming technology outsourcing hub. My best bet is to outsource to him.

It is true that tens of thousands of immigrants from US, Canada and Europe have been returning to their native countries lately to take advantage of the outsourcing boom. Since they understand the western business and consumer culture, it is definitely easier to deal with them relative to their local competitors who lack that cultural knowledge firsthand, although the latter group could be technically as qualified. The flip-side to this scenario is that those returning folks tend to have much higher financial expectations in line with their prior western lifestyles, often making their services significantly costlier than their counterparts. My personal experience has been that their services are not only costlier but their quality is hardly any better than the less-fancy local competitors. So, instead of blindly signing up with your old friend, have at least ten more competitors price out your RFP. Thus, you will get a better understanding of the real price point. Once you start with a partner it is not easy to part, so look before you leap. Worse yet, many of those returning immigrants are unable to assimilate back into their old culture, often causing their businesses to fold and consequently will leave you totally in the lurch. On the other hand, when a less glamorous local competitor fails, it is generally due to the business reasons. Again, I am not opposed to being sympathetic to the old friend, but at the end of the day, take the right business decision.

2. In order to keep my outsourcing costs down, I have decided to hook up with a group of programmers rather than software engineers. I have dealt with both here and I found no difference except in costs.

That may very well be true here although I cannot vouch for it as I haven’t dealt with them separately here. But in those countries both groups compete in the same space for the same jobs, thus significantly blurring the differences in costs. In fact, I have dealt with both groups separately there and have found the software engineers vastly superior to their counterparts. As I research those outfits, I use keywords like software engineers. They not only understand the requirements better and faster, but they also offer better suggestions in creating the overall application. Since they understand the specs better, they tend to make fewer mistakes, minimizing unnecessary interactions. They are also less argumentative when changes and corrections are cited. So my suggestion would be to look for a growing company headed by software engineers, preferably classmates from the engineering school. Therefore, the chemistry as well as the knowledge base would be there, without the extra costs.

To read the rest of this piece, please consider my new book "Bailing Out the Dysfunctional Civil Service System." This is one of the bonus pieces in the book.

Please click on the title above to preview the book.

Homequant.com Introduces Vastly Enhanced Free Home Valuation on the Net

2011-06-19T11:26:00.005-04:00

PRESS RELEASE

Homequant.com is designed to offer an alternate (unlike a traditional appraisal or a BPO) home valuation system so users can experiment with and arrive at their own value conclusions.

New York, NY, June 17, 2011 --(PR.com)-- Announcing the re-launch of vastly enhanced Homequant.com – the art and science of valuing a single family on the net. Instead of offering some old frozen values, Homequant.com is designed to empower its users with an innovative way to value a residential property.

All one needs to know is the name of the neighborhood and an approximate size and age of the subject property. Homequant.com then helps simulate the subject, match the recent comparable sales, and produces a valuation report that looks more like a professional comps report, including a complete analysis of the value parameters.

And everything is in plain English, presented in an easy-to-understand format, without the usual appraisal mumbo-jumbo. And, it’s all free and requires no registration or login whatsoever.

Homequant.com is not only an excellent market knowledge tool for the current and future homeowners, but it is also great for analysts, appraisers, assessors, brokers, hearing officers and mortgage professionals needing sample values or quick validation of the existing values, without having to use a professional valuation system or a proprietary listing services. Additionally, the macro ‘Sales Query’ module will help visitors understand the econometrics of the broader markets.

Homequant.com is developed by an industry expert with 20+ years of expertise in appraisal research and automated valuation modeling.

If you’d like more information about this website, or to schedule an interview with them, please call 718-314-4081 or email them at: contact@homequant.com

Contact Information
Homequant
Sid Som
718-314-4081
sidsom1@yahoo.com
www.homequant.com

Source: http://www.pr.com/press-release/332222

Why Simulated Subjects Will Soon Dominate the CMA Market

2011-04-09T11:09:00.005-04:00

On the heels of the recent housing market meltdown, the mortgage originators today are lot more careful from the beginning of the process – not only in pre-approving the borrower, but also in better understanding the true worth of the collateral. During the last housing frenzy many loan officers used to be perfectly satisfied with any model-driven automated values or even far inferior basic Comparative Market Analysis (CMA) or Broker Price Opinion (BPO) values to originate the process. Today, those values are used with a grain of salt. In fact, in most cases, they require advanced CMA’s that incorporate a series of automated yet statistically meaningful market adjustments to the comps, mimicking actual appraisals. Unfortunately, one such CMA report obtained online from an outside vendor generally cost $49.95 which, of course, does not replace an appraisal. Loan officers need more flexibility and significantly better price point for the mortgage origination to be more competitive and efficient.

In traditional CMA world two populations (databases) are maintained – subjects and sales, though some vendors supplement sales with the listings data (outside the purview of this piece). Let’s assume that a CMA vendor supports only the single family residences (“SFR”) and closed sales. If county X has a population of 500K SFRs and generally generates 3% sales annually, the vendor has to carry a sales database of 30K (usually recent two years of sales are meaningful) in addition to the 500K population database. Since the vendors compile and maintain the population databases by purchasing/sourcing the data from multiple sources – from assessing jurisdictions to specialized spatial/mapping companies to Tiger files, etc. – this maintenance of the population databases becomes extremely expensive, thus pushing the individual CMA prices irrationally high as well.

Here come simulated subjects. Since loan officers have access to the subject’s information in the mortgage application and could also be verified from the public records – from location to property characteristics to special upgrades, etc., they can easily enter that into an application creating a simulated subject which could then be easily valued by the standard comparables process meaning by having them valued by properly matched and adjusted comps from the sales database, thereby eliminating the need for the maintenance of the expensive juggernaut, i.e., subjects database. Once valued, the simulated subject becomes the subject. Thus, instead of having to maintain two separate databases containing 530K parcels for one county, only one database of 30K would effectively do the job. Since the miscellaneous information like demographics and soft/survey statistics - needed for appraisals - are however frills for CMAs. Therefore, the elimination of the subjects’ database would not create any conflict there either.

Let’s try to analyze the pros and cons of the traditional CMAs using actual subjects vis-à-vis CMAs with simulated subjects:

1. Carrying Cost of Subjects’ Data: As discussed earlier, the carrying cost of the subjects’ data is enormous. The national data vendors that carry data for most counties (more than 3,000 counties in the US) spend tens of millions of dollars to carry that data. The smaller CMA vendors who tend to acquire that data from the national vendors also spend a small fortune (except for alternative arrangements like joint venture, revenue sharing, etc.). This high cost of carrying subjects obviously gets factored into the CMA prices. On the other hand, if all subjects are simulated, this expensive layer could be easily dispensed with, significantly lowering the cost of the CMAs.

2. The Quality of CMAs: The non-existence of the subjects’ data in a CMA database does not lower the quality of the CMA in any respect. Since that information is shown in the sales contract and is readily available in public records (even in non-disclosure states) and as such could be easily entered into a computer program to have it valued by comparable sales, it is more a matter of tradition and esthetics rather than a logical market necessity. Of course, if the CMA vendor is also involved in developing and selling model-driven values (MRA, Optimization, Neural Network, AEP, etc.), then the subject population becomes a necessity as those models need to be applied to value the unsold population. Of course, in this piece I am making a case that the future CMA vendors should be standalone to avoid having to carry the subject population in order to offer CMAs at a significantly reduced price to their clients, particularly the volume buyers.

3. The Quality of Subjects’ Data: Since the hedonic data come from the assessing jurisdictions that tend to recollect data on a longer cycle, generally four to six years – often much longer, a big chunk of the subjects’ data is therefore unreliable. The flawed subject data on the CMA (often multiple iterations are needed to correct the data) often slows the approval process down. On the other hand, the simulated subjects’ data could be spot on – easily obtained from the seller (or seller’s agent or lawyer) and verified by the buyer and public records, leaving no room for error or guesswork and thus speeding up the approval process. Just think about it: CMA is not a rocket science. All one needs are some basic data elements – fixed neighborhood, externals and GIS, quantitative and qualitative property characteristics, and special upgrades, if any. In any case, a CMA is not an appraisal. The final issuance of a first mortgage would always be contingent upon an actual appraisal performed by a qualified appraiser. Considering all this, the simulated subject CMAs off of the consensus data from both buyer and seller would be more appropriate, keeping costs vastly down yet improving the speed and accuracy of the process.

4. The Quality of Sales Data: In a stable to rising market most sales are “dressed and staged” meaning most sellers tend to make some changes, minor cosmetic to gut rehab, to their properties before putting them up for sale. Generally, the listing agent advises the seller as to what changes could maximize the marketability of the property. Therefore, often there is a bimodal distribution between the comparable sold and the unsold properties in terms of their respective effective ages. Assessing jurisdictions in charge of the property inventory are also aware of those changes from the listing databases. As we all know, local tabloids love to sell assessment sensationalism as property taxes often constitute one of the largest recurring expenditures for the property owners. To avoid having to deal with any negative publicity in terms of at least the inventory discrepancy of the recently sold properties (generally an easy catch for the tabloid folks), assessing personnel always attach high importance to keep the inventory of the sold properties up-to-date. Therefore, subject data on the CMAs are often outdated while sales data are current. This anomaly could be avoided by simulating the subjects on the CMAs.

5. Sales Database is only 10% of the Population: Since only 3 to 5% of the SFR’s generally sell in a given year, the active 2-year sales database would thus comprise only of 6 to 10% of the entire population. In other words, by simulating the subjects the remaining 90% of the database could be made redundant, thereby greatly reducing not only the cost of the data, but the high cost of the database administration (DBA salaries, etc.) as well. Although most data vendors carry 5 to 10 years’ of sales, only the recent 2 years’ (ideally preceding one year) of sales would be meaningful to generate CMAs for the simulated subjects. As we are valuing one subject at a time here, no representative sales sampling – as required in automated valuation modeling – would be needed to create the CMA sales databases.

6. Neighborhood Adjustment: Neighborhood adjustments at the CMA level are better done by the local real estate professionals than by the MRA coefficients from the automated valuation models which often proxy other variables as well. Local professionals study and use the differential outcome (parametric differences in sale prices between neighborhoods) to adjust the comps that are selected from other neighborhoods than those of the subjects’. When neighborhood data are unavailable, Census Tracts and Blocks should be used as they are established research nodes. Since neighborhood adjustments are either manually entered relative to each subject or are anchored in a separate table connected to the adjustment grid, there are no special advantages of maintaining the separate subjects’ database. When the neighborhood data are used to adjust comps, the neighborhood name along with the (simulated) subject’s address must be entered. In turn, the geo coding of the address would return the Latitude and Longitude, as well as the Census Tracts and Blocks, making them totally application-driven. No doubt, while having access to the concurrent subjects database makes this a real convenience, the trade-off must be considered.

7. Time Adjustment: Time adjustment makes time (different sale dates for comps) irrelevant. Therefore, when comps are time-adjusted, it makes no difference whether they come from the same quarter/year or from different quarters. Since time is a surface correction, time coefficients must be developed by quarter (to maintain enough liquidity and smoothness) and by broader market-tiers (see my earlier piece on time adjustments for details) and then anchored into the adjustment grid. Once the newer sales are added and the older sales are dropped every month, time coefficients must be updated. Again, unlike neighborhoods, time has nothing to do with the subject population so it makes no difference whether the subjects are concurrently read off the active database or are simulated. While most practitioners understand the need for proper time adjustments in AVM, they often treat time irrationally in CMA’s. Time must be treated the same way in both modes of valuation.

8. Distance Adjustment: Like the neighborhood adjustments, distances are computed off the subjects. Since addresses are always manually entered for the simulated subjects, distances are automatically derived (from address to latitude/longitude to distance), requiring no additional manual effort. Even within the same neighborhood, distances are individually scored – comps in closer proximity get more positive treatment than their distant counterparts. A priori, this is another convenience of having direct access to the subjects database as long as the Latitude and Longitude (often maintained mutually exclusively of the addresses) are also correct. If they are incorrect and they often are, the distance adjustment could be grossly wrong. So, this is not necessarily a big plus to have the separate subjects’ database in place to generate CMAs.

9. GIS/Externals/Micro Location Adjustment: The economic influences of fixed neighborhoods and micro location are not necessarily collinear. Even within an excellent school district some houses may be fronting railroads or major arteries, having negative impact on prices. Conversely, within the same school district, some houses may be fronting a beautiful lake or a park (we all know the economic influence of Central Park on Manhattan coops and condos), fetching significantly higher prices. While the national data vendors tend to carry the waterfront data, the GIS/externals/micro location data are generally absent in their databases. In fact, considering the significantly smaller size of the sales populations, the micro location data could be easily collected at desktop using generic GIS software, enhancing the effectiveness of such sales databases manifold. Of course, collecting that data for the entire subject population (100+ million homes in the US) would be very expensive and time-consuming. However, while simulating the subject that information could be easily entered (from a drop-down) to have it reflected in the value, as long as sales are also cured and adjustment grids are updated as such. So, this is a big plus for having the subjects simulated.

10. Pricing of CMA’s: Today vendors charge between $29.95 and $49.95 for a quality CMA (with statistical adjustments) because of the high costs associated with maintaining the monolithic subjects’ populations. If that maintenance could be meaningfully disposed of, monthly subscription (per county) might significantly fall, perhaps equaling the current price of handful individual CMAs. The savvy vendors should reinvest part of the savings in collecting the micro location data for the sold population to enhance the quality and reliability of CMAs as a whole. No doubt, in no time the CMA prices would come down to a point where the CMAs off of the simulated subjects’ could effectively compete with even (modeled) AVM values as long as the requirements are totally bottom-up, i.e., valuing one subject at a time. Of course, AVM values would be superior if the required solution is top-down, i.e., at the population level.

(click on the table to get an enhanced view)

Sid Som’s Case Studies

Case # 1: My wife and I are deeply indebted to New York City. Our kids have used NYC Public schools to go on to top colleges like Harvard, etc. So, in an effort to do something for the fellow NYC residents, my wife invented the concept of the “Simulated Subjects.” Her current public service home-site namely Homequant.com (live connection on the sidebar) is the first attempt of valuing simulated subjects with actual comparable sales. This site is meant for non-professionals so it is presented in a pretty straight forward manner, although it is quite powerful. It has two modules – Valuation and Sales Query. Valuation is the micro module to value one simulated subject at a time, while the Sales Query is the macro module showing economic properties at a neighborhood, etc. level. An upgraded and more graphical version is currently being developed which would cover other major markets as well. The upgraded version will also allow more flexible adjustments for comps, as well as better market stats.

Case # 2: I am working on a professional version which I expect to debut this summer, as well as showcase in national conferences later in the year. The professional version will be made available strictly on subscription basis – unlimited use by county – to the private sector clients. While the user will enter the actual street address and neighborhood/district (where available) of the subject, the derivative spatial and census data would be retrieved by the application. It will also feature a very powerful yet easy to use adjustment grid allowing adjustments for Time, Neighborhood/District, Waterfront, Size (land, building, etc.), Bath Count, Style, Story, Exterior Wall, Grade, Condition, etc. A powerful sales analysis module will also be provided to help analyze the broader market sales as well as the other data variables – quantitative and qualitative. All standard CMA reports – comps analysis and value parameters, spatial definitions of subjects and comps, aerial pictures, etc. – will be part of the package. Stay tuned.

Again, no first mortgage is ever underwritten without an actual appraisal. CMAs are done at the front-end to facilitate the underwriting process. The traditional CMA costs and prices are unreasonably high due primarily to the traditional maintenance of the entire subject populations, although a very small percentage of which is generally used in valuation. To bring those costs and prices significantly down, we need to switch to the simulated subjects. The future is here!

Thanks,

Sid Som
sidsom1@yahoo.com

The US Housing Market Faces Double-Dip

2011-02-27T20:24:00.014-05:00

The housing economists and researchers tend to follow three major periodic sales statistics to gauge the health of the overall US market, two of which represent the existing (pre-owned) housing stock while the third one reflects only the new stock. Of course, the size of the existing housing market way outweighs its new counterpart – more like 90% to 10%. Although both the National Association of Realtors (“NAR”) and S&P/Case-Shiller (“Case-Shiller”) publish the existing stats monthly, their methodologies -- please refer to my earlier posts for details -- are so vastly different that they often educate the interested by bringing competing market trends and perspectives. On the other hand, considering the illiquidity in the new home sales market the US Census Bureau (“Census”) publishes the stats on a quarterly basis.

This piece has now been adopted in my new book "How to Predict US Housing Markets with Case-Shiller Indices." Please click on the title above to access the book.

Thanks,

Sid Som
sidsom1@yahoo.com

Reviving and Reshaping the US Housing Industry

2011-01-17T01:25:00.001-05:00

A total overhaul is needed in order to revive the ailing US housing industry. The existing laws and industry practices are antiquated to the point that they are dragging the industry further down. The overhaul is undoubtedly way overdue so Congress needs to act now if it really believes in fostering home ownership. The following ten changes are necessary, now:

1. Defining Primary Residence: While many federal and state guidelines lump one, two, three and four family properties as primary residences, only legal single family residences, individual coops and condos (collectively and hereafter, SFR) should be considered as primary residences. The universe of two, three and four family homes is income producing and therefore must be treated as such. Instead of treating this universe as “all” commercial, it may be treated as “semi” commercial. Nevertheless, we should not confuse the issue here – this group must be separated from the SFR’s to create the right level of “risk” verticals to assess cost of mortgages.

2. Promoting Primary Residence: In order to promote home ownership we need to differentiate between the primary residency ownership and speculative ownership. Only the purchases leading to the establishment of primary residences should qualify for SFR mortgages. All non-primary, speculative purchases - although often SFR’s - requiring financing must be directed to the commercial (semi-commercial if you would) market, thus protecting and promoting true home ownership. Granted, the speculators also add liquidity to the market, but their inherently different objective necessarily introduces the short-term greed and frenzy, ultimately hijacking the market and destroying the foundation of home ownership.

3. Arms-length Sales: Only those sales that meet Fannie and Freddie’s internal AVM criteria – irrespective of individual appraisal – should qualify for normal “SFR” mortgage terms. As we all know, appraisal fraud is part and parcel of any housing frenzy; therefore, the establishment of these AVM criteria will not only validate the underlying collateral, but they will also help minimize appraisal frauds. Banks will have the discretion of either declining the non-arms-length sales altogether or treating them with different risk parameters. Of course, Fannie and Freddie’s in-house AVMs are arguably not the most efficient ones so they have to step up to the plate to improve their effectiveness.

4. Credit Worthiness: Assessing a borrower’s credit worthiness is critical in the mortgage industry. While a number of private credit rating companies offer scoring services to the mortgage originators, the appropriate federal agency should also develop scoring models and generate free scores for all eligible citizens to stabilize the industry. Additionally, considering the generally subjective nature of the scoring models, the industry under the guidance of the federal agency producing the champion scores should move to a range-ranking to interject a level of fairness into the system. For example, a range-ranking system may look like this: score 800 & above; 750 to 799; 700 to 749; 650 to 699; 600 to 649; 550 to 599; 500 to 549; under 500, etc. Thus, the scores from the competing models (challenger scores) would be statistically more significant and comparable. Again, given the subjective nature of the existing models, the model scores often vary by 30 to 60 points causing confusion and inequity. In case of confusion in terms of the competing scores (wildly diverging ranges), the federal range must be used to be fair to the borrower.

5. Enough Skin in the Game: In order to foster a true home ownership climate, policy makers have to make sure the potential borrowers are entering into the contract with adequate skin in the game. The low down and low docs spell disaster. So, just the way no home buying should ever be encouraged with less than 20% down payment, limited documentation would open up the backdoor for the speculators. There is no room for either in the SFR mortgage market. The self-employed must also prove that they have enough net income to qualify. Since credit scores and down payment are inversely related, borrowers with only high credit ranges (700+) would qualify for the low 20% down payment. Conversely, those with blemished credit (under 600) must have more skin in the game (60% down) than the lender (40%). PMI is therefore a thing of the past. FHA’s current low down (as low as 3.5%) and loose qualification will only create another bubble, rather than promoting home ownership. Innocent taxpayers must not be on the hooks to bailout the unqualified homeowners.

6. Mortgage Insurance: Just the way no mortgage is issued without a title search, no mortgage should be issued without mortgage insurance either, irrespective of the level of down payment and/or credit score ranges. Moreover, it cannot be a rider or wrap around to an existing life or casualty insurance – it must be underwritten separately by an approved vendor of the lender only and assigned to the lender at closing so the premium is annually collected as part of the escrow. Obviously, the mortgage insurance premium would be collinear with the mortgage risk. If every mortgage is thus protected by a renowned insurer collecting enough premiums, the secondary market could rest easy as well, without having to worry about the liquidity of the originators.

7. Mortgage Interest Deduction: The mortgage interest deduction on the SFR must be withdrawn. It simply shifts the economic burden on to the renters and homeowners who do not carry mortgages. The discontinuance might encourage owners to pay off the loan balances faster, prompting accelerated equity which is universally welcome. Contrary to the old economics, an investment in an SFR is an asset class by itself in owner’s asset allocation model. Like stocks and bonds, an SFR has its own market risk. Just the way stocks and bonds are easily hedged nowadays, the value of an SFR against a declining market could be appropriately hedged via derivative instruments at options exchanges.

8. Capital Gains and Losses: The existing lax laws on capital gains and losses from the sale of primary residences encourage a trading mindset instead of furthering long-term perspectives of home ownership. We need new laws that would require a “seven year rule.” Under this proposed rule, an SFR owner must live there at least seven years to avoid having to pay taxes on capital gains or write off losses. The slower turnover of these properties will stabilize the neighborhoods and will help arrest the falling prices. Before the seven year period, the owner’s capital gains will be taxed as ordinary incomes – a discouraging penalty indeed. Since capital gains/losses is a key investment driver, this law will set the pseudo investors and speculators seriously back, perhaps forcing them out of this market completely.

9. Real Estate Taxes: While the mortgage interest deduction should be withdrawn, the homeowners will however continue to deduct the real estate taxes as they are used by the local governments to provide common services – from public schools to libraries to fire stations to sewage, etc. The real estate taxes paid is a “social” deduction benefitting the society, while mortgage interest is an “individual” deduction benefitting the property owner only. Any slide in those services will have an equal and opposite reaction, lowering the quality of life, the pride of ownership, and invariably the home prices. Considering the eroding tax base most local governments are increasingly confronted with, any reversal of this deduction could be totally counter-productive.

10. Home Equity Loans: The same “seven year rule” must apply to the home equity loans, HELOCs and “Juniors”. Within the first seven years of the primary mortgage, no home equity loans, regardless of the equity, must be authorized. This will prevent homeowners from trading on the early stage equity. During the recent housing frenzy millions of homeowners took out their entire equity – based on inflated and unsound appraisals – from their primary residences to invest in second and third homes in anticipation of quick and hefty returns, thereby nicely positioning themselves on ticking foreclosure time bombs. Today, the outcome is jaw-dropping: In 2010, a record 2.9 million properties received foreclosure filings!

If we are serious about the revival of the US housing industry, we need to make these structural changes. No denial, these are some of the gutsiest changes ever envisioned and proposed!

Thanks,

Sid Som
sidsom1@yahoo.com

Should the Taxable Status Date be Forward or Backward?

2010-12-18T12:30:00.005-05:00

While most property assessment experts are wrestling with the frequency of the assessment cycle, meaning whether properties should be assessed annually or every three years, etc., I have a completely different perspective on this issue.

Proper market information and data hold the key to produce a fair and equitable roll. The real estate market, like the stock market, has become extremely volatile (rises fast or declines fast), making it increasingly difficult to produce a futuristic roll with the backward-bending market data. Since the taxable status date is generally a futuristic date, the available market information and data tend to be quite inadequate to develop proper predictive (mass appraisal) models that, in turn, generate the assessment roll. Case in point: Most taxing jurisdictions utilizing mass appraisal modeling generally build their models in August and September with the available data, targeting the next January 2 as the status date (assuming the valuation and status dates are the same). At that point, because of the usual 3-month lag in recording and validation of sales, the most recent sales in the modeling file would cover, at best, June-July, leaving an enormous predictive gap of at least six months. Worse yet, a vast majority of those arm’s length sales would have been contracted in the first and early second quarter of the year, leaving a small percentage of the questionable investor/distressed cash sales to represent the recent state of the market.

With a market as volatile as this, and considering the structural shift to higher risk-taking resulting in continued higher volatility going forward, those futuristic rolls are tantamount to crap-shoots in the name of mass appraisal modeling. Granted, today we have more mass appraisal experts all around the world, thanks to organizations like IAAO, as well as more advanced econometric and operations research techniques, but the higher modeling expertise and advanced techniques could not be the proxy for the lack of market data around the status date. Simply put, nobody has the crystal ball in simulating a volatile market six to nine months in the future. That experimentation would be okay to write a thought-provoking paper or article, but is totally unacceptable to experiment with an assessment roll involving most taxpayers’ biggest financial investment.

Again, the only way assessing jurisdictions can achieve the goal of a fair and equitable roll under the changing market conditions (let's face it, market volatility is here to stay) is if they move away from the predictive mode and settle for a known event. While most mass appraisal modelers understand the basic MRA process, they do not truly understand the advanced econometric modeling. Therefore, the guesswork in the name of predictive modeling forces the modelers as well as their management to undertake a gigantic gamble forecasting values way out in the future.

After having spent, off and on, twenty years in mass appraisal, I have come to the conclusion that the dialogue should be about the taxable status “date” – should it be a forward date or a backward date? I am of the opinion that it should be a...

To read the rest of this piece, please consider my new book "Bailing Out the Dysfunctional US Property Tax System."

Please click on the title above to preview the book.

Analyzing New Home Sales Statistics

2010-12-12T09:49:00.011-05:00

The US Census Bureau in joint collaboration with the US Dept. of Housing and Urban Development (HUD) publishes the new home sales statistics monthly. Considering that the new home sales market is a small subset (12% - 15%) of the overall market, the stats are therefore tracked and analyzed on a quarterly roll-up, ensuring reasonable underlying liquidity to the comparative stats and the resulting metrics. In addition to the general sales count and the median sales price, the stats are also broken down by the region as well as the type of financing, adding more depth to the stats. Regional stats are especially important as the national stats are not necessarily representative of the respective regions.

(please click on the image to get an enhanced view)

The graph shows how the new home sales volume (along with pre-owned homes which is the theme of a prior post) has also fallen off the cliff since the top of the housing frenzy – between 2006 and 2010 the volume has plummeted 68% (from 1,051,000 to 340,000). Due to the ongoing illiquidity in the Jumbo market, the fall in the long end of the value curve is truly incredible. Since the Q4 Nov-Dec sales are unavailable as of this writing, I have recycled the seasonally compatible Q4-2009 to proxy the Q4-2010, although I expect the actual volume to be lower as many buyers had rushed in Q1-Q2 to take advantage of the expiring homebuyer credit. By the way, these are all survey statistics so the relative standard error (RSE) is always compact in the body of the distribution curve (where data collection is generally more predictable and consistent), tending higher in the outer ends of the curve. Again, the lower the RSE, the more reliable the estimates.

Again, due to the unavailability of Q4-2010 median prices, the Q3 prices have been used to proxy 2010. All said and done, the actual Q4 prices will be significantly lower. Case in point: “The median sale price of new houses sold in October 2010 was $194,900.” The seasonally-low November and December will drag the median further down, perhaps around $185,000. Using Q3-2010 as the 2010 index, the national median has declined 12% between 2006 and 2010, although West and Northeast have already experienced much larger declines of 23% and 22%, respectively. If the Q4 national median falls to $185,000, the decline would be 25%. The higher RSE and the lower price collinearity with the other regions make Northeast housing market somewhat less predictable. Given the current no-job-and-income-growth economic recovery, the 2011 housing market – both new and existing – will see further erosion in price levels.

The above table is jaw-dropping. Between 2006 and 2010, while the conventional financing for new homes declined from 90% to 60%, the government guaranteed FHA and VA simply exploded – from a mere 6% to an astounding 35%. Considering the significantly lower qualification criteria (3.5% down, lower FICO, etc.) for these guaranteed mortgages, unfortunately this explosion translates to another housing bubble in the making. In view of the builder liquidations, cash purchasers have not only kept pace, but are expected to do even better in 2011 as prices further decline and liquidations climb.

This table is double jaw-dropping. While the conventional mortgages moved in tandem with the market, the FHA and VA completely bucked the trend and continued to finance increasingly higher median prices amid the collapsing market. At the top of the market in 2006 FHA conservatively financed a median price level of $146,200, but in the midst of the continuing market collapse in 2010 they have aggressively upped the ante to $188,200. Either their “Rip Van Winkle” analysts are fast asleep at the switchboard following in the footsteps of Fannie and Freddie, or they are chivalrous enough to predict the imminent housing boom. Either way, as they wake up from their chivalrous dream, the taxpayers would foot a small bill – in excess of a trillion!

Thanks,

Sid Som
sidsom1@yahoo.com

Data sources:
http://www.census.gov/const/www/newressalesindex.html
http://www.census.gov/const/newressales.pdf

Current State of Commercial Real Estate Loans

2010-11-21T20:15:00.007-05:00

While there are hosts of data sources to evaluate commercial real estate in the US, the most reliable data and analyses, unquestionably, are contained in the quarterly publication titled ‘Charge-off and Delinquency Rates on Loans and Leases at Commercial Banks’ from the Federal Reserve. The publication contains the two most important macro metrics – Charge-off rate and Delinquency rate – that are central to the understanding of the health of commercial real estate loans. To make matters easier, the publication even breaks the results down between all commercial banks and the largest 100 banks making and carrying such loans.

To understand the difference between the charge-off rate and delinquency rate as well as the banks in question, let’s zero in on the definitions as offered by the Federal Reserve:

“Charge-offs, which are the value of loans removed from the books and charged against loss reserves, are measured net of recoveries as a percentage of average loans and annualized.”

“Delinquent loans are those past due thirty days or more and still accruing interest as well as those in nonaccrual status. They are measured as a percentage of end-of-period loans.”

“Banks are insured U.S.-chartered commercial banks. Size, where used, is measured by consolidated assets adjusted for mergers; where used, other banks (ignored in this article) are those smaller than the 100 largest.”

Simply put, the charge-off rate is historical while the delinquency rate is ongoing. Therefore, they are mutually exclusive. The combined rate is naturally more consequential in depicting the total picture. On a related note, the correlation between the two is .94, a near perfect collinearity, and therefore almost predictive of each other. The following table and chart will demonstrate how the health of the commercial real estate in the US is becoming increasingly anemic, thus preventing the economy from recovering from its current misery and perhaps pushing it back into a double-dip.

(please click on the image to get an enhanced view)

The combined charge-off and delinquency rate has jumped from 1.55% in 2007-Q1 to 12.221% in 2010-Q3 – an astounding 688% spike. In fact, the rate has more than doubled (5.76% to 12.22%) since the Lehman collapse in Q3-2008. At this rate, by the end of this year, the commercial real estate industry may easily approach a jaw-dropping combined rate of 13%. And, depending on the level and pace of unfreezing of the credit market and the reopening of its CMBS counterpart, it may easily exceed 15% by Q4-2011. While the current charge-off rate is still hovering under 3.0%, going forward it will rise at a much faster pace as a result of the exponential growth in delinquencies in 2009. A vast majority of those delinquencies will be charged off in Q4-2010.

The very existence of the commercial real estate industry largely depends on the availability of financing. During the recent credit bubble, those who were able to finance their properties with minimum skin in the game would be out of luck now if confronted with a balloon falling due. Therefore, the properties/owners requiring refinancing are considered more or less distressed. Many flagship commercial properties are being auctioned off at or below fifty percent of their prior sale prices at the top of the market. The point is, the conventional valuation metrics like rental rates, vacancy rates, expense ratios and cap rates would hardly matter if the need for an immediate financing is on the table. Unfortunately, even if the banks are willing to refinance, the new appraisal may push the LTV to a point the deal would be untenable.

At the municipal finance level, the assessors should seriously research and consider the availability of financing to reduce exposure to their municipal budgets. For example, if the current median LTV in their local market is down to 60% from the prior 80%, the cap rate may by increased by two percentage points. While lowering the value of the properties on the roll does not generally translate to lower revenue (target revenue is generally a function of tax rates), it nonetheless reduces the budget exposure and, in turn, the future tax refund liability.

The Congressional Oversight Panel's report "Commercial Real Estate Losses and the Risk to Financial Stability" raised some serious concerns, “Between 2010 and 2014, about $1.4 trillion in commercial real estate loans will reach the end of their terms. Nearly half are at present “underwater” – that is, the borrower owes more than the underlying property is currently worth. Even borrowers who own profitable properties may be unable to refinance their loans as they face tightened underwriting standards, increased demands for additional investment by borrowers, and restricted credit.” The Congressional Oversight Panel is “deeply concerned that commercial loan losses could jeopardize the stability of many banks, particularly the nation’s mid-size and smaller banks, and that as the damage spreads beyond individual banks that it will contribute to prolonged weakness throughout the economy.”

Thanks,

Sid Som
sidsom1@yahoo.com

Data sources:

http://cop.senate.gov/reports/library/report-021110-cop.cfm
http://www.federalreserve.gov/releases/chargeoff/

Using Pending Home Sales Index as a Leading Housing Activity Indicator

2010-11-07T16:45:00.009-05:00

Of the various closely-watched monthly housing indices – new home sales, existing home sales, pending home sales, housing starts, mortgage applications, Case-Shiller, etc. – only the pending home sales is a leading housing indicator, while the rest of the pack are essentially lagging indicators.

According to National Association of Realtors (NAR), “Pending Home Sales Index (PHSI) measures housing contract activity. It is based on signed real estate contracts for existing single-family homes, condos and co-ops. A signed contract is not counted as a sale until the transaction closes. Since pending home sales measure actual existing-home sales, the PHSI provides an accurate and reliable indicator of future home sales activity. Our sample shows that over 80% of all pending home sales go to settlement within a 2-month time-period (and a significant share of the rest close in month 3 and month 4).”

The PHSI is available for the overall US market, as well as the four regional markets namely, Northeast, Midwest, South and West. While the indices are available both seasonally adjusted and unadjusted, the latter, unlike the existing home sales where the seasonal adjustment is more meaningful, is a better predictor of the actual market activity. Therefore, the unadjusted data series, along with other meaningful variations, have been chosen for this study.

(click on the image to get an enhanced view)

After having fallen to an all-time low of 63.2 in December 2009 the US index skyrocketed to 133.4 in April 2010 due entirely to the renewed and expanded homebuyer credits (qualification: contracted by April 30 and closed by September 30). Since the expiration of those credits the index has been steadily declining. The preliminary September 2010 index shows a 15% plunge from the prior month. The Northeast series is even more telling: after having plunged to 42.4 in December 2009 the index zoomed to 124.8 in April 2010 and has since collapsed again to 50.1 in September 2010 indicating an astounding 24% month-over-month decline. At this rate, the December 2009 low could be easily retested by the end of the year. The pictures relative to Midwest and South are unfortunately analogous to Northeast’s. However, the West has been a story of resounding bounce back. In fact, it is heartening to note that their August 2010 index far exceeded the April 2010 index, demonstrating that they managed to stay away from the homebuyer credit hoopla. No denial, the renewal and extension of the homebuyer credit, aided by the (exploding) cheap FHA mortgages, paved the way for another housing bubble, the recent bursting of which will necessarily set the stage for a new wave of foreclosures in the future.

Instead of looking at the kinked monthly data series most economists would prefer somewhat smoother data series by introducing the moving average – in this case the 3-month moving average. The national as well as the regional index continue to depict the same picture as the original series, although the most recent month-over-month plunges have significantly moderated. While the Northeast still leads the decline, the West now shows a 3.4% growth, staying above the April-May hoopla. Therefore, given the rapid rates of decline in recent months the Northeast and the Midwest markets have the greatest likelihood to collapse, particularly going into the seasonally-low Q1. The Jumbo market could be hit harder.

Moving averages and standard errors always go hand in hand. This table shows how the standard errors started to peak in tandem with the moving averages. As the averages peaked in April-May, the standard errors also spiked from the low-to-mid teens to the low-to-mid twenties, except for the West where, as indicated earlier, the homebuyer credit did not contribute to a bubble. For the South the error jumped from a low 13.35 in February to 31.51 in May but has collapsed to 7.20 in September.

Again, the PHSI is an excellent leading indicator to gauge the existing housing activity, even in a tight credit market as this where perhaps every other pending sale – especially the Jumbo – fails to consummate. Therefore, in order to understand the overall housing market this leading index must be studied in addition to the Case-Shiller index which is inherently lagging.

Thanks,

Sid Som
sidsom1@yahoo.com

Data source:
http://www.realtor.org/research/research/phsdata

The Often Overshadowed House Price Index

2010-10-17T19:56:00.014-04:00

While the S&P/Case-Shiller home price index is the de facto standard for the broader market, the Federal Housing Finance Agency’s (FHFA) House Price Index (HPI) is an excellent indicator of the conforming market. Therefore, the Case-Shiller and the FHFA indices are not necessarily comparable – that is, “apples to apples” – indices. In fact, the latter could be construed as a subset of the former. Nevertheless, housing economists and analysts follow this quarterly index as keenly because it also provides them “with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas.”

“The HPI is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. The HPI includes house price figures for the nine Census Bureau divisions, for the 50 states and the District of Columbia, and for Metropolitan Statistical Areas (MSAs) and Divisions.”

Since the recent housing meltdown and the resulting Fannie/Freddie bailout, I have been eagerly following this index especially to tract the movement of house prices of the so-called foreclosure states (meaning AZ, CA, FL, and NV). As we all know, these four sunshine states experienced the most dramatic rise and fall in prices during the recent (2002-09) housing frenzy. So, let’s see what this index had in store for these states during that period.

(please click on the image to get an enhanced view)

The above graph shows very similar price movements for all of these four states – rapidly rising between Q2-2002 and Q1-2006 and falling off-the-cliff since tapering off in Q1-2007. Although visually they look like bell curves, the underlying data series are not normally distributed. In a normal distribution, the kurtosis - the peakedness of the distribution - is 3, whereas the series kurtosis here range from -1.1849 to -1.4724. To be statistically more specific, AZ and FL trends decouple themselves at the top and continue to skew negatively. AZ and FL trends therefore almost duplicate each other, whereas CA and NV are in lockstep until very recently. Unfortunately, despite the two rounds of homebuyer tax credits and a host of other government stimuli including mortgage modifications and foreclosure halts, AZ, FL, and NV prices have continued to fall steadily, while CA prices lately have moved sideways showing some signs of renewed life. To test an alternate hypothesis, if the Q1-2000 starting points were all reset to 100 (in reality: AZ 149; CA 111; FL 131; NV 124), the four price curves would closely overlay one another, evening out the aforesaid split-tops. Due to these split-tops, the two trends need further exploration mutually exclusively.

Volatility Analysis

While there are various measures to quantify volatility, the coefficient of variation (standard deviation normalized by mean) is used here considering the normal data series. If a group of people without formal education in statistical methods was shown the above two graphs and was then asked to point to the area of higher volatility, most of them would point to the middle of the graphs showing the rapid rise and decline of prices. However, contrary to this conventional wisdom, the extended curve – all 42 quarters – shows significantly higher volatility than the middle of the curve which, regardless, truly reflects the steep rise and fall of the market. Broken out as the head and two shoulders (FHFA tables - right), the head has the lowest measure of volatility followed by the left and right shoulders. Again, because of the negative skewness, the right shoulder has somewhat higher volatility than the left shoulder.

Since this index covers only the conforming market, it must be used as such. In other words, it should be used in addition to the Case-Shiller index to additionally validate that segment of the mortgage market. On the other hand, in view of the HPI’s extensive geographic coverage, it is an excellent add-on where Case-Shiller is still unavailable.

Thanks,

Sid Som
sidsom1@yahoo.com

Data source:
http://www.fhfa.gov/Default.aspx?Page=87

Understanding Moody’s/REAL Commercial Property Price Index (CPPI)

2010-10-09T22:12:00.009-04:00

Like the S&P/Case-Shiller Home Price Index, the Moody's/REAL Commercial Property Price Index (CPPI) is widely followed by economists and researchers in understanding the movement of US commercial real estate prices. Since both of these indices are based off of similar repeat sale methodology, many experts often overlay them on each other to ascertain the direction of the respective markets and the collinearity of the resulting risks. However, given their inherently different economic properties, I have decided to exclude the overlay of the home price index from the purview of this post.

The CPPI index “is designed to track same-property realized round-trip price changes based purely on the documented prices in completed, contemporary property transactions. The index uses no appraisal valuations. The methodology employed to construct the index is a repeat-sales regression (RSR).” Even the appraisal community which tends to primarily use income and cost approach to value commercial properties, not only follows this family of indices closely, but often borrows these coefficients to develop time adjustments for their comps, local to national. Considering the number of competing periodic and one-off studies and data sources on the market, CPPI indices are more statistically accurate, consistent and reliable and, as such, they are more defensible in courts. Therefore, professional appraisers would be better off with these time coefficients than the limited-focus studies periodically put together by brokerage houses (generally using their in-house sales only, aided by the lack of their knowledge of statistics/econometrics).

Although the index was originally developed in partnership with MIT’s Center for Real Estate (MIT CRE) to support the trading of commercial property price derivatives, it has since received such widespread private and public recognition that it has now become the de facto leading economic indicator of the commercial real estate market, particularly in defining and quantifying its general direction and price trends. In addition to achieving enormous market acceptance among traders and portfolio and fund managers, the ongoing partnership with MIT CRE has also given the index the global academic and political visibility. Over the years, the partnership has also helped develop other meaningful derivative indices, not only for trading but for real estate benchmarking as well.

(Please click on the image to get an enhanced view)

The above graph is just awe-inspiring. The rapid rise and the diabolical fall of prices would be an economist’s predictive nightmare. Between Q4-2000 (index=100) and Q3-2007, the cumulative growth in prices was 90% (CPPI hit an all-time high of 191.87 in October, 2007) - a remarkable feat indeed. Unfortunately, the fall has been even more remarkable, perhaps even frightening. The virtual free fall of commercial real estate prices, resulting primarily from the unavailability of proper financing as well as the frozen CMBS market, has become a ticking economic time bomb, threatening the sustainability of any economic recovery in the near future. Between October, 2007 and July, 2010 (most recent index available), the index declined a jaw-dropping 43.20%. Except for a short “dead cat bounce” (Nov 2009 to May 2010), the index recently returned to its downward spiral. Unless the index reverses its course quickly, in Q4-10 it may easily fall below 100 – meaning the Dec 2000 price level. Just imagine the renewed curve!

Even the comparative graph shows the prices across the major categories (apartment complex, industrial, office and retail) moved up more or less in lockstep. Apartment complex consistently outperformed its competitors while office properties showed slightly lesser rate of growth. Again, on the way down, they enjoyed the party together. Lately, the apartment complex – big beneficiary of the housing meltdown – has been showing some signs of green shoots, but whether they will turn yellow going forward remains to be seen.

During the frenzy years (2002-07) the NY Metro office properties enjoyed an average annual return of 15%, while SoCal, DC and San Francisco earned 13%, 10% and 5%, respectively. Conversely, in 2009 alone, NY experienced a whopping 33% negative return, followed by DC, SoCal, and San Francisco. Of course, the half-full picture would be the fact that their overall returns for all nine years (2001-09) are still positive. In other words, those who had bought office properties back in 2001 are generally above water.

The Congressional Oversight Panel's oversight report "Commercial Real Estate Losses and the Risk to Financial Stability" raised some serious concerns, “Between 2010 and 2014, about $1.4 trillion in commercial real estate loans will reach the end of their terms. Nearly half are at present “underwater” – that is, the borrower owes more than the underlying property is currently worth. Even borrowers who own profitable properties may be unable to refinance their loans as they face tightened underwriting standards, increased demands for additional investment by borrowers, and restricted credit.” The Congressional Oversight Panel is “deeply concerned that commercial loan losses could jeopardize the stability of many banks, particularly the nation’s mid-size and smaller banks, and that as the damage spreads beyond individual banks that it will contribute to prolonged weakness throughout the economy.”

Thanks,

Sid Som
sidsom1@yahoo.com

Data Sources:
http://www.rcanalytics.com/derivatives_index.aspx
http://cop.senate.gov/reports/library/report-021110-cop.cfm

Analyzing Existing Home Sales Statistics

2010-09-25T20:02:00.012-04:00

“The NATIONAL ASSOCIATION OF REALTORS® Existing-Home Sales Series is the premier measurement of the residential real estate market. On or about the 25th of each month, NAR releases statistics on sales and prices of existing single-family homes for the nation and the four regions. These figures include condos and co-ops, in addition to single-family homes.”

While other existing and new home sales market data and statistics are available from different private and public sources, NAR’s existing home sales data and statistics truly comprise the gold standard in this domain and are therefore very closely watched and followed by economists and analysts around the world. In fact, any major deviation between the actual and the forecasted monthly data and/or revisions to the prior data often tend to have significant impact on that day’s activity in the stock as well as the derivative markets.

The following analyses will demonstrate how to use this data series to evaluate and predict the future housing trends relative to the volume, price, and months’ supply of the overall US and the regional markets.

SALES VOLUME

(please click on the image to get an enhanced view)

The volume chart shows two modes – 2009-11 and 2010-04 – that resulted from the two recent expirations of the homebuyer credits. In other words, while the overall US volume is down 26% from the recent high (of 2009-11), the regional markets are down between 30% (West) and 45% (Midwest). The impact of the credit was thus very short-lived, forcing a chunk of sales being borrowed from future months. The Q4-10 and Q1-11 have no other option but to follow the downward trend, perhaps accelerated, additionally considering the seasonality of the housing market. The correlation matrix is quite predictive: While the regional markets are highly correlated with the overall US market and Northwest, Midwest and South are also highly correlated among themselves, West divorces itself from the rest, particularly Northeast. Simply put, West will not necessarily move in tandem with the other three regional markets.

SALES PRICE

Again, as the homebuyer credit expired, 2010-08, the most recent month, shows all around weakness in prices – not a single region bucks the trend. Except Northeast, the 2010-08 price levels of the other regional markets as well as the US are at or below the 2009-08 price levels, proving the theory of the reversion to the mean. Again, as the volumes revert to the normal levels and seasonality dominates, the Q4-10 and Q1-11 will see significant price erosions. The correlation matrix here is more telling though: Although Northeast price direction shows a low level of correlation with the overall market, it has virtually no correlation with the other regional markets. The median price in Northeast jumped 15% in recent four months – from 226,500 in 2010-05 to 260,300 in 2010-08. If the other markets have already reverted to the mean, Northeast will be no exception. It has therefore more downside risk in next two quarters than the other three. Investors be aware!

MONTHS' SUPPLY

Months’ supply is a traditional market metric professionals use to determine if it is a buyer’s or seller’s market. Traditionally, 6 months’ supply is considered neutral meaning that the market forces are in equilibrium. Going by that theory, the housing market, overall, is totally out-of-sync and heavily tilted towards to buyers in the wake of the mounting inventory. As expected, months’ supply and sales volume are highly (negatively) correlated, almost to a point that they are predictive of each other (for example, 2009-11 vs. 2010-07). As the market was artificially propped up, price shows a somewhat anomalous relationship with both volume and months’ supply, which will be corrected in next two quarters. Of course, if the current Administration decides to rob Peter to pay Paul again – a.k.a. bailout – the all-too-familiar irrational exuberance will return, forcing the market into a period of imbalance, all over again.

Reverting to the mean, a few correlation matrices can be enormously helpful to understand the interplay among the competing markets.

Thanks,

Sid Som
sidsom1@yahoo.com

Data Source: http://www.realtor.org/research/research/ehsdata

Explosion of FHA-Insured Mortgage Defaults

2010-09-04T22:03:00.017-04:00

FHA mortgages are guaranteed by the Federal Housing Administration, a division of the Department of Housing & Urban Development (HUD) but are underwritten by approved third party financial institutions. The lenders are therefore protected against all borrower defaults. FHA mortgages are generally the easiest to qualify for. The FHA guidelines for qualification are the most flexible of all mortgages that often require only 3.5% down payment, lower FICO score, financeable closing costs, etc.

However, the recent changes to the qualification criteria require a 10% down when the borrower’s FICO is below 580. “New FHA borrowers must have a minimum credit score of 580 to qualify for the FHA’s most favorable down payment plan, currently at 3.5%. Borrowers with credit scores of less than a 580 FICO score will be required to put at least 10% down. It’s important to understand that having a credit score of less than 580 does NOT disqualify applicants from getting an FHA loan, but the down payment requirements are stricter under the announced guidelines.”

While the FHA-insured originations have skyrocketed in recent years – from a mere 3% in 2002 to a whopping 35% in recent months – the default rates of those mortgages have been exploding as well. The July-2010 FHA report shows a 90-day default rate of 8.32% on single family insured portfolio, up from 7.77% a year ago and 6.11% in October, 2008. In other words, the default rate jumped 221 basis points in 22 months. Worse yet, in last one year while the FHA originations jumped 23%, delinquencies soared an alarming 31.5%.

(click on the image to get an enhanced view)

The aforesaid 8.32% default rate is an aberration though, on the heels of the gold rush to take advantage of the expiring homebuyer credit (condition: contracted by Apr 30, 2010 and closed by Sep 30, 2010). A more normal picture (relative to the market) could be had if we shift the spotlight on to a neutral month like Jan-2010 which was not terribly influenced by this chase. The Jan-2010 default rate was 9.40%, a stick higher than the current rate. In fact, as we return to the normal market behavior resulting in far fewer originations due to lesser demand in Q4-2010, the normal default rates will quickly take over. Case in point: The July NAR Existing Home Sales report indicated 27.2% month-over-month and 25.5% year-over-year plunges in sales.

As this lower demand gets reflected in the shrinking origination base, the default rate will have no other choice but to soar. On the other hand, the fast-shrinking yet competing private mortgage insurances requiring significantly higher qualifications will return to the Jan level again, pushing primarily the lower quality originations off to the FHA bucket. Unfortunately, sub-prime mortgages, e.g., 580 to 650 FICO, are still being promoted and insured by the FHA, with a low 3.5% down. Considering the minimum skin in the game, the FHA borrowers do not see any reason to prepay their mortgages either – amply reflected in the falling prepayment trend.

Even the above regression run (in log form) shows that the "default" independent variable is the most significant one judging the significance level by the T-stat, signaling the pent-up rise in the default rate ahead given the growing spread between originations and delinquencies.

Finally, the 30- and 60-day delinquencies have not been factored in here. While the 30-day delinquencies are often revolving, the 60-day ones are almost as incurable as their 90-day counterparts. Even if we factor in just 50% of the 60-day delinquencies, the shadow default rate becomes 12.48%. Then again, if the 9.40% hypothesis comes to pass by the end of Q4-2010, the shadow default rate jumps to 14.1%. Add another year to this scenario, and you would be dealing with a shadow rate of at least 18%. Hopefully, the bailout would start much earlier, to avoid having to deal with a juggernaut like the ongoing Fannie/Freddie ordeal.

Thanks,

Sid Som
sidsom1@yahoo.com

Data Sources:
FHA Policy Changes You Should Know About
http://www.fha.com/fha_article.cfm?id=151
Monthly Report to the FHA Commissioner
http://www.hud.gov/offices/hsg/rmra/oe/rpts/com/commenu.cfm

Manhattan Condo and Coop Market Trends

2010-08-08T12:48:00.010-04:00

In addition to the financial markets, Manhattan is known around the world for its glitzy condo and coop markets. The prewar coops on the Upper East Side and modern high-rise condos are the envy of even the rich and famous. Coining those addresses in their portfolios is often a necessity for them. In fact, even during the Great Recession of 2009, 75 condos and coops fetched over $10M each. Because of this global demand, the Manhattan market has not only consistently outperformed the other major condo markets like Los Angeles, Las Vegas, and Miami, but it has also recovered from various downturns considerably faster than the competition.

Unlike condos where owners own real estate, coop owners own shares in coop corporations that, in turn, own the buildings. Shareholders are granted the right to occupy their units via a proprietary lease which is similar to an occupancy agreement. Since the coop corporations pay for the buildings’ underlying mortgages, property taxes, and insurances and then pass them through to the shareholders, the monthly coop maintenance charges tend to be significantly higher than the comparable common changes for the condos. Then again, condo owners are directly responsible for their property taxes and insurances. The vast majority of upscale coop corporations (and their boards) in Manhattan has very stringent acceptance requirements, thereby keeping the potential investors away. On the other hand, even the most prestigious Manhattan condo buildings often allow non-primary residences, thus maintaining liquidity by attracting investors from around the globe.

For this piece, since I have considered only the elevator condo and coop buildings, Manhattan’s other architectural residential masterpieces – turn-of-the-century brownstone and sandstone walkup buildings, many of which were later converted to coops – have not made this cut. Additionally, I have ignored the actual market data for the first two quarters of 2010 considering they are more market aberrations than normal market behaviors on the heels of the then-active homebuyer credits. The normal market behavior should return in the second half of the year, correcting the anomalous data of the first half, at which point the actual 2010 data (or part thereof) could be considered in market analyses. Until then, the projected data for 2010 are more meaningful. Therefore, the 2010 data shown in the following charts are trended off the prior data.

(please click on the image to get an enhanced view)

Between 2003 and 2008, condo prices literally doubled. As the prices started to rise and the financing was quite easy to come by, the market kept attracting more buyers. In fact, between 2000 (not shown) and 2007, the sales volume also doubled, making this market one of the most liquid condo markets in the world. Although the volume skidded 46% since peaking in 2007, the median prices have only moderately declined. The steep drop-off in the volume resulted from the ongoing credit squeeze – unfortunately, the multifamily ownership market has been more severely hurt. The anecdotal evidence shows that the softness is more visible in the luxury (>=$5M) market than in the lower or mid-end of the value curve, thus preventing the median to fall off the cliff; whereas, during the recent housing tsunami, the other major condo markets encountered an across-the-board shakeout, causing the median to pancake as well. While my polynomial trends show some more downside potential in both volume and price in 2010, the next two years should see some meaningful market consolidations and consequently sideways price movements.

The coop market also showed significant strength – 70% price gain –
between 2003 and 2008. Conversely, the volume has fallen 44% since its recent 2007 peak. Again, because of the primary residence requirement in coops, they are inherently less speculative than the condos. As a result, the price gains in the coop markets tend to lag those in the condo markets. The recent credit squeeze has been impacting coops more than the condos, so the recovery in the coop market is going to be relatively slow as well. Unlike the condo market, the coop market may not see any price consolidations until late 2012. Of course, the positive aspect of the Manhattan coop market is that there is no new supply (no new conversions), whereas even at the bottom of the recession, the influx of the new high-rise condos adds to the existing glut, further misbalancing the condo market equation. The softness in the luxury market is equally pronounced here: In 2007, 159 $5M+ sales took place, while that volume plummeted to 76 in 2009.

I must reiterate that the metallurgy of the Manhattan condo and coop market is inherently different from the competition. It is a global marketplace, always enticing buyers from far and wide. No doubt, it succumbs to recessions and downturns, but it recovers way ahead of the others. The current downturn will pose no exception either.

Thanks,

Sid Som
sidsom1@yahoo.com

Data Source: NYC Department of Finance
Link: http://www.nyc.gov/html/dof/html/property/property_val_sales.shtml

Health of Residential Real Estate Loans

2010-07-17T21:24:00.007-04:00

While there are hosts of data sources to evaluate residential real estate loans in the US, the most reliable data and analyses, unquestionably, are contained in the quarterly publication titled ‘Charge-off and Delinquency Rates on Loans and Leases at Commercial Banks’ from the Federal Reserve. The publication contains the two most important macro metrics – Charge-off rate and Delinquency rate – that are central to the understanding of the health of residential real estate loans. To make matters easier, the publication even breaks the results down between all commercial banks and the largest 100 banks making and carrying such loans.

To understand the difference between the charge-off rate and delinquency rate as well as the banks in question, let’s zero in on the definitions as offered by the Federal Reserve:

“Charge-offs, which are the value of loans removed from the books and charged against loss reserves, are measured net of recoveries as a percentage of average loans and annualized.”

“Delinquent loans are those past due thirty days or more and still accruing interest as well as those in non-accrual status. They are measured as a percentage of end-of-period loans.”

“Banks are insured U.S.-chartered residential banks. Size, where used, is measured by consolidated assets adjusted for mergers; where used, other banks (ignored in this article) are those smaller than the 100 largest.”

Simply put, the charge-off rate is historical while the delinquency rate is ongoing. Therefore, they are mutually exclusive. The combined rate is naturally more consequential in depicting the total picture. On a related note, a near perfect collinearity of .96 between the two is almost predictive of each other. The following table and the chart will demonstrate how the health of the residential real estate loans in the US is becoming increasingly anemic, thus preventing the economy from recovering from its current misery and perhaps pushing it back to a double-dip.

The combined charge-off and delinquency rate has jumped from 2.21% in 2007-Q1 to 15.32% in 2010-Q1 – an astounding 593% spike. In fact, the rate has more than doubled (7.28% to 15.32%) since Lehman Bros. collapsed in Q3-2008. At this rate, by the end of this year, the residential real estate loans may easily experience a jaw-dropping combined rate somewhere between17% and 18%, depending on the level and pace of unfreezing of the credit market and the reopening of its MBS counterpart. While the current charge-off rate is still hovering around 3%, going forward it will rise at a much faster pace as a result of the current exponential growth in delinquencies. Case in point: The delinquency rate jumped 45% between 2009-Q1 and 2010-Q1 (8.73% to 12.65%).

Considering the imminent tsunami of the 2007 resets (3-year adjustable rate mortgages originated in 2007) coupled with the elevated unemployment levels, the delinquency rates are only expected to get worse in 2010-11. In an effort to better manage the portfolio risks, banks are now demanding significantly higher down payments and FICO scores (as compared to the recent housing frenzy years) as well as more meaningful appraisals, resulting in far fewer originations and a steadily shrinking mortgage base. Obviously, as the base shrinks, the delinquency rate would worsen. While the FHA-insured loans have propped up the conforming market in last two years, unfortunately the delinquency rate in that segment has been rapidly rising, the impact of which could further shock and awe the projected delinquency rates.

Of course, the Jumbo market is a different story altogether. Banks are very reluctant to take on that added risk as the securitization market is still more or less shut down. Until the MBS returns to life again, the Jumbo market will continue to suffer and remain illiquid. The anecdotal evidence shows, even the recovering mortgage REITs are unwilling to invest in that market segment. The Jumbo loans are critical in vast majority of the coastal markets – often comprising 40% to 60% of the local market. The illiquidity in those predominantly Jumbo markets has been dragging the median prices down. For example, according to the local MLS, the median price of Queens (NYC borough) has fallen from $400K in Sept-2008 to $306K in May-2010. Unfortunately, those markets are stuck in a vicious downward cycle – falling prices, rising risks, unwilling lenders, continued illiquidity, rising seller nervousness, falling prices, and so on.

Again, to get to know the health of the residential real estate market, one should seriously follow the movement of the combined charge-off and delinquency rates of the residential real estate loans. The steady rise in those rates will continue to discourage lenders from the required risk-taking, dampening any hopes of the housing recovery in the near future.

Thanks,

Sid Som
sidsom1@yahoo.com

Data Source: Federal Reserve's Statistical Release
Link: http://www.federalreserve.gov/econresdata/releases/statisticsdata.htm

Explosion of FHA and VA Mortgages

2010-05-18T22:38:00.009-04:00

While the new home mortgage market is quite small relative to the existing home mortgage market, it is nonetheless representative of the overall home mortgage market. Therefore, the new home mortgage statistics used in this study amply paints the picture of the overall single family home mortgage market. Since the beginning of the recent housing market meltdown, the mortgage market has been going through a structural transformation in terms of new originations. At the bottom of the recent housing frenzy in 2002, the combined FHA and VA insured mortgages represented roughly 3% of the overall market; they account for a whopping 35% now, reshaping the entire mortgage landscape.

FHA and VA mortgages are guaranteed by the respective government agencies but are underwritten by approved financial institutions. The lenders are therefore protected against all borrower defaults. FHA mortgages are generally the easiest to qualify. The FHA guidelines for qualification are the most flexible of all mortgages that often require only 3.5% down payment. VA mortgages, on the other hand, are meant for those who are currently serving in the United States military or are honorably discharged. These mortgages are typically available for no down payment.

(click on the image to get an enhanced view)

The table/chart demonstrates how these two government agencies, since the collapse of Bear Stearns and Lehman in 2008, essentially stepped in and took over the responsibility of new originations from the private financial institutions. In 2006 and 2007, FHA and VA collectively originated 6% and 7% respectively, while they suddenly exploded to 22% in 2008 and 33% in 2009. While the preliminary Q1-2010 stats already show a modest year-over-year projected growth, some are forecasting significantly higher combined total – around 40% to 45%.

Amazingly, between 2006 and 2009, the new home originations dropped 64%. Therefore, the absolute numbers are more jaw-dropping to follow: These two agencies originated only 63,000 out of a total of 1,051,000 new home mortgages in 2006; whereas in 2009, an astounding 124,000 out of 375,000 were originated by them. Hypothetically, if these government programs were not shored up and had stayed at the 2007 level, the total new home originations in 2009 might have been well under 300,000. Unfortunately, despite a significant surge in recent foreclosure inventory, even cash investors have stayed away from investing their own money considering that the FHA money lately has been remarkably easy to tap into.

(click on the image to get an enhanced view)

The above tables show even scarier situation. As the home prices started to come down from the peak of the frenzy in 2006-07, the median prices financed by FHA and VA steadily climbed. In fact, between 2006 and 2010-Q1, new home prices plummeted 12%, while VA and FHA median financed prices soared 16% and 26% respectively. The FHA default picture is particularly troublesome. The 90-day default rate is approaching an alarming 9%. Just add the less-publicized 30 and 60-day delinquencies, and you have a new disaster in the making.

Robert Toll, the CEO of the largest U.S. luxury homes builder Toll Brothers Inc., recently remarked at a New York conference, “Yesterday’s subprime is today’s FHA. It’s a definite train wreck and the flag will go up in the next couple of months: Bail us out. Give us more money.”

Thanks,

Sid Som
sidsom1@yahoo.com

Data Sources:
http://www.census.gov/const/www/newressalesindex.html
http://www.hud.gov/offices/hsg/comp/rpts/com/commenu.cfm

Use Case-Shiller Index to Examine Vital Stats of Ailing US Housing Market

2010-05-02T16:24:00.009-04:00

Dear Readers,

This piece has been replaced by a new chapter with updated data and analysis in my new book "How to Predict the US Housing Market with Case-Shiller Indices." To learn more about the Case-Shiller indices, please read the book. To access the book, please click on the title page above.

Thanks,

Sid Som
sidsom1@yahoo.com

Health of Commercial Real Estate Loans - Revisited

2010-04-24T13:37:00.006-04:00

While there are hosts of data sources to evaluate commercial real estate in the US, the most reliable data and analyses, unquestionably, are contained in the quarterly publication titled ‘Charge-off and Delinquency Rates on Loans and Leases at Commercial Banks’ from the Federal Reserve. The publication contains the two most important macro metrics – Charge-off rate and Delinquency rate – that are central to the understanding of the health of commercial real estate loans. To make matters easier, the publication even breaks the results down between all commercial banks and the largest 100 banks making and carrying such loans.

To understand the difference between the charge-off rate and delinquency rate as well as the banks in question, let’s zero in on the definitions as offered by the Federal Reserve:

“Charge-offs, which are the value of loans removed from the books and charged against loss reserves, are measured net of recoveries as a percentage of average loans and annualized.”

“Delinquent loans are those past due thirty days or more and still accruing interest as well as those in nonaccrual status. They are measured as a percentage of end-of-period loans.”

“Banks are insured U.S.-chartered commercial banks. Size, where used, is measured by consolidated assets adjusted for mergers; where used, other banks (ignored in this article) are those smaller than the 100 largest.”

Simply put, the charge-off rate is historical while the delinquency rate is ongoing. Therefore, they are mutually exclusive. The combined rate is naturally more consequential in depicting the total picture. On a related note, the correlation between the two is .95, a near perfect collinearity, and therefore almost predictive of each other. The following table and the chart will demonstrate how the health of the commercial real estate in the US is becoming increasingly anemic, thus preventing the economy from recovering from its current misery and perhaps pushing it back to a double-dip.

(click on the image to get an enhanced view)

The combined charge-off and delinquency rate has jumped from 1.55% in 2007-Q1 to 12.91% in 2009-Q4 – an astounding 803% spike. In fact, the rate has more than doubled (6.02% to 12.91%) since the Lehman collapse in Q3-2008. At this rate, by the end of this year, the commercial real estate industry may easily experience a jaw-dropping combined rate ranging somewhere between 15% and 18%, depending on the level and pace of unfreezing of the credit market and the reopening of its CMBS counterpart. While the current charge-off rate is still under 3.5%, going forward it will rise at a much faster pace as a result of the current exponential growth in delinquencies.

As we all know, the very existence of the commercial real estate industry largely depends on the availability of financing. During the recent credit bubble, those who were able to finance their properties with minimum skin in the game would be out of luck now, if confronted with a balloon coming due. Therefore, the properties/owners requiring refinancing are considered more or less distressed. Case in point: A flagship Boston office property was recently auctioned off at fifty percent of its prior sale price. The point is, the conventional valuation metrics like rental rates, vacancy rates, expense ratios and cap rates would hardly matter if the need for an immediate financing is on the table. Unfortunately, even if the banks are willing to refinance, the new appraisal may push the LTV to a point the deal would be untenable.

At the municipal finance level, the assessors should seriously research and consider the availability of financing to reduce exposure to their municipal budgets. For example, if the current median LTV in their local market is down to 60% from the prior 80%, the cap rate may by increased by two percentage points. While lowering the value of the properties on the roll does not generally translate to lower revenue (target revenue is generally a function of tax rates), it nonetheless reduces the budget exposure and, in turn, the future tax refund liability.

Randall Zisler, chief executive officer of Zisler Capital Partners LLC, in a recent report titled “A crisis of unprecedented proportions is approaching” estimated that building owners may default on $500 billion to $750 billion of mortgage debt – as much as 54 percent of the $1.4 trillion in loans coming due in four years. The report added, “Much of the debt is likely worth about 50 percent of par, or less. Many banks will end up insolvent as they reduce the value of their holdings.”

Data Source: http://www.federalreserve.gov/releases/chargeoff/

Thanks,

Sid Som
sidsom1@yahoo.com

Examining Vital Stats of US Commercial Real Estates

2010-01-02T13:07:00.010-05:00

Like the S&P/Case-Shiller Home Price Index, the Moody's/REAL Commercial Property Price Index (CPPI) is widely followed by economists and researchers in understanding the movement of US commercial real estate prices. Since both of these indices are based off of similar repeat sale methodology, many experts often overlay them on each other to ascertain the direction of the respective markets and the collinearity of the resulting risks. However, given their inherently different economic properties, I have decided to exclude the overlay of the home price index from the purview of this post.

The CPPI index “is designed to track same-property realized round-trip price changes based purely on the documented prices in completed, contemporary property transactions. The index uses no appraisal valuations. The methodology employed to construct the index is a repeat-sales regression (RSR).” Although the index was originally developed in partnership with MIT’s Center for Real Estate to support the trading of commercial property price derivatives, it has since received such widespread private and public recognition that it has now become the de facto leading economic indicator of the commercial real estate market, particularly in defining and quantifying its general direction and price trends. In addition to achieving enormous market acceptance among traders and portfolio and fund managers, the ongoing partnership with MIT CRE has also given the index the global academic and political visibility. Over the years, the partnership has also helped develop other meaningful derivative indices, not only for trading but for real estate benchmarking as well.

Even the appraisal community which tends to primarily use income and cost approach to value commercial properties, not only follows this family of indices closely, but often borrows these coefficients to develop time adjustments for their comps, local to national. Considering the number of competing periodic and one-off studies and data sources on the market, CPPI indices are more statistically accurate, consistent and reliable and, as such, they are more defensible in courts. Therefore, professional appraisers would be better off with these time coefficients than the limited-focus studies periodically put together by brokerage houses (generally using their in-house sales only, aided by the lack of their knowledge of statistics/econometrics).

(click on the image to get an enhanced view)

The above chart is just awe-inspiring. The rapid rise and the diabolical fall of prices would be an economist’s predictive nightmare. Between Q4-2000 (index=1.00) and Q3-2007 the cumulative growth in prices was 90% (CPPI hit an all-time high of 1.9187 in October, 2007) - a remarkable feat indeed. Unfortunately, the fall has been even more remarkable, perhaps frightening. The virtual free fall of commercial real estate prices, resulting primarily from the unavailability of proper financing as well as the frozen CMBS market, has become a ticking economic time bomb, threatening the sustainability of any economic recovery in the near future. Between October, 2008 and October, 2009 the national index of all properties fell an astounding 36.4%, while it declined a jaw-dropping 43.7% from its October, 2007 peak.

Even the comparative chart shows the prices across the major categories (apartment complex, industrial, office and retail) moved up more or less in lockstep. However, on the way down, retail lately has been showing some signs of green shoots, but whether they will turn yellow going forward remains to be seen.

During the frenzy years (2002-07) the NY Metro offices enjoyed an average annual return of 15%, while DC, SoCal and San Francisco earned 12%, 13% and 6% respectively. Conversely, in 2009 alone, NY experienced a whopping 38% negative return, followed by SoCal, DC and San Francisco. Of course, the half-full picture would be the fact that their overall returns for all eight years (2002-09) are still positive. In other words, those who had bought office properties back in 2002-03 are still above water.

Randall Zisler, chief executive officer of Zisler Capital Partners LLC, in a recent report titled “A crisis of unprecedented proportions is approaching” estimated that building owners may default on $500 billion to $750 billion of mortgage debt – as much as 54 percent of the $1.4 trillion in loans coming due in four years. The report added, “Much of the debt is likely worth about 50 percent of par, or less. Many banks will end up insolvent as they reduce the value of their holdings.”

Thanks,

Sid Som

Data sources:
http://www.rcanalytics.com/derivatives_index.aspx
http://mit.edu/cre/research/credl/rca.html
http://www.sco.ca.gov/Press-Releases/2009/11-09summary.pdf

Should the Taxable Status Date be Forward or Backward?

2009-12-19T11:43:00.013-05:00

While most property assessment experts are wrestling with the frequency of the assessment cycle, meaning whether properties should be assessed annually or every three years, etc., I have a completely different perspective on this issue.

Proper market information and data hold the key to produce a fair and equitable roll. The real estate market, like the stock market, has become extremely volatile (rises fast or declines fast), making it increasingly difficult to produce a futuristic roll with the backward-bending market data. Since the taxable status date is generally a futuristic date, the available market information and data tend to be quite inadequate to develop proper predictive (mass appraisal) models that, in turn, generate the assessment roll. Case in point: many taxing jurisdictions utilizing mass appraisal modeling generally build their models in August and September with the available data, targeting the next January 2 as the status date (assuming the valuation and status dates are the same). At that point, because of the usual 3-month lag in recording and validation of sales, the most recent sales in the modeling file would cover, at best, June-July, leaving an enormous predictive gap of at least six months. Worse yet, a vast majority of those arm’s length sales would have been contracted in the first and early second quarter of the year, leaving a small percentage of the questionable investor/distressed cash sales to represent the recent state of the market.

With a market as volatile as this, and considering the structural shift to higher risk-taking resulting in continued higher volatility going forward, those futuristic rolls are tantamount to crapshoots in the name of mass appraisal modeling. Granted, today we have more mass appraisal experts all around the world, thanks to organizations like IAAO, as well as more advanced econometric and operations research techniques, but the higher modeling expertise and advanced techniques could not be the proxy for the lack of market data around the status date. Simply put, nobody has the crystal ball in simulating a volatile market six to nine months in the future. That experimentation would be okay to write a thought-provoking paper or article, but is totally unacceptable to experiment with an assessment roll involving most taxpayers’ biggest financial investment.

Again, the only way assessing jurisdictions can achieve the goal of a fair and equitable roll under the changing market conditions (let's face it, market volatility is here to stay) is if they move away from the predictive mode and settle for a known event. While most mass appraisal modelers understand the basic MRA process, they do not truly understand the advanced econometric modeling. Therefore, the guesswork in the name of predictive modeling forces the modelers as well as their management to undertake a gigantic gamble forecasting values way out in the future.

After having spent, off and on, twenty years in mass appraisal, I have come to the conclusion that the dialogue should be about the taxable status “date” – should it be a forward date or a backward date? I am of the opinion that it should be a...

To read the rest of this piece, please consider my new book "Bailing Out the Dysfunctional US Property Tax System."

Please click on the title above to preview the book.

Building Permits and Housing Starts Must Continue to Fall Through 2010-11

2009-12-12T21:35:00.008-05:00

The statistics on new building permits and housing starts are reported monthly by the Commerce Department and are generally considered leading economic indicators. More importantly, the new permits have always helped define and lead the housing cycles, while housing starts have helped us understand the actual pipeline.

During the recent housing frenzy (2002–06), the volume of new permits and housing starts had skyrocketed in certain markets in anticipation of the pent-up demand – mostly the investor–led speculative demand. Likewise, that pace has substantially cooled as the market started to decline since 2006–07. Given the glut of the existing inventory, this trend must continue through 2010–11 for the housing market to hit any sort of natural bottom.

Because of the recent explosion in FHA mortgages aided by the homebuyer’s credit, the current housing market is obviously not a natural market driven by the true market forces of demand and supply. In fact, we will return to a somewhat natural market once that credit expires in April, 2010 and the growing FHA-bubble is at least heeded to.

Meanwhile, to take advantage of this artificial credit environment, some overly optimistic builders would be expected to jump in and open new permits and even get started. Of course, if this market suddenly dips again when this life support is withdrawn, foreclosures could re-emerge with harsher venom, tipping the existing glut off the cliff. Then, this new inventory will have to compete with the mounting foreclosures dragging the new home prices significantly down. Banks’ current unwillingness to underwrite construction loans will simply worsen.

(please click on the image to get an enhanced view)

As you can see, at the peak of the recent housing frenzy, permits and starts exceeded 2M annually, but deteriorated to 1.4M in 2007 and 905K in 2008. At the current rate, the 2009 volume is expected to settle around 600K – an astounding 70% decline from their respective frenzy peaks. The regional picture is somewhat mixed. Since the speculative bubble was bigger in South and West, the 2009 housing start stats are understandable (around -50%).

Nonetheless, this is an excellent trend and it must continue through 2010 and 2011 allowing the existing inventory to be absorbed. Ideally, the housing start stats should be well under 500K (perhaps 300K in 2010 and 400K in 2011) to allow these 'green shoots' to take any significant root. Of course, if the housing market double-dips in late 2010, any new inventory as a result of these starts would be menacing to the market.

Thanks,

Sid Som

Data sources:
US Dept. of Commerce
National Association of Home Builders

Dynamics of Manhattan Condo Market

2009-12-06T21:41:00.007-05:00

Since Manhattan is the financial capital of the world, its residential condo market has always been highly sought-after, locally as well as by global investors. In fact, because of its true global demand, the Manhattan condo market has consistently outperformed the other major condo markets in the US. Moreover, Manhattan has the advantage of being a small built-up island so it rarely succumbs to any significant supply glut.

Although the Manhattan multifamily market consists of both condos and co-ops, I have intentionally removed the latter from this analysis considering its inherently restrictive nature of ownership. Also, I have considered the sales in elevator condo buildings only. While condo owners own the real estate, co-op owners, on the other hand, own shares in the co-op corporation only. In the process of fostering primary residency, Manhattan co-ops seriously discourage investor ownership, forcing the demand to be more local and hence quite limited. By the way, in many other parts of the world, condos are alternatively known as ownership apartments or ownership flats.

Needless to say, Manhattan condos are some of the priciest on earth. In fact, even in this declining market, in 2009, 30+ condos fetched over $10 million each in sale prices – ranging in prices between $10M and $37.5M each. A vast majority of the units that sell for $1M+ generally belong to the full service, high-rise buildings. Comparable units in the same building on higher floors tend to fetch significantly higher prices depending on the view as well as the level of noise. The ones on the higher floors either having river views or overlooking the central park are considered the crown jewels of the Manhattan condo market.

(click on the image to get an enhanced view)

From the above table and the chart, it is evident that the Manhattan condo market has been facing some softness, although lately it has been flat-lining. Between 2008-Q1 and 2009-Q4, prices have declined 15% to 17%, depending on how you evaluate the market – decline in absolute prices or price per square feet. This decline is quite insignificant when compared with declines in other international markets in the US, e.g., Los Angeles, Las Vegas and Miami where the declines from their peaks have exceeded 40%.

Of course, if I apply the equity market theory to the real estate market, I readily notice a significant downside potential considering that the median price has not only broken through the $1M psychological support, but the $1,000 price per square feet support is also on the brink of being broken through. Whether you agree or disagree with this line of thinking, the combination of the illiquidity in the high-end condo mortgage market and the lack of a psychological price support can significantly dampen the bottoming of this market, at least for a while.

Thanks,

Sid Som

Data source: NYC Dept. of Finance website

Why Investors Should Study Price-Income Ratios to Assess Market Risk

2009-11-28T18:39:00.015-05:00

Since home sales and household income data are easily available nowadays, the price-income ratio study has become one of the most routine top-line studies informed investors tend to undertake to ascertain the investment risk at the market level. Recent home sales information can be obtained directly from the county clerk’s/recorder’s office or from a host of private commercial sources, while the income data can be obtained from the census files, as well as from the private sources.

In fact, for the purpose of this study, I obtained both sales and income data for free. While I downloaded the Queens sales data from the NYC Finance site, I extracted the median household income data from MS MapPoint 2009 which comes loaded with the demographic data as well. Additionally, I used Zip code as the comparative geo-metric, but other geographic metrics like census tract/block, town, schools, etc. may also be used. Considering Zip code is a routing metric, census tract is inherently a better metric as it is also more econometrically-oriented.

Of course, Zip code offers more flexibility in terms of the market roll-ups and drill-downs. In other words, Zip codes can be easily rolled up to the leading three digits to construct a broader market, or they can be drilled down to the Zip plus four to address a thinner market. I used the leading three Zip codes to keep the study at the broader market level, thus fifty something Queens Zip codes were reduced to only five leading three Zip codes.

A word of caution: The objective here is market risk analysis, not portfolio risk analysis. Obviously, to analyze the level of risk of a given portfolio involving specific parcels, a recent AVM would be appropriate. On the other hand, price-income ratios should initially be studied to determine if a particular market, or segments thereof, conform to the investor’s risk tolerance. More in-depth studies should follow when the initial price-income ratios are in line with the investor’s risk guidelines.

To develop an AVM, a representative sales sample involving four to eight quarters (depending on the liquidity of the local market) of sales would be needed, whereas the price-income ratio study necessarily entails simulating the most recent market so sales pertaining to the most recent two quarters should suffice. Consequently, I have used only the 2009-Q2/Q3 sales in this analysis.

The above table and chart demonstrate that even within a county the risk spread, as defined by the price-income ratio here, could be significant. In fact, the market segment representing the leading-3 Zip 111 has almost three times higher risk than its 110 counterpart, alerting investors of the potential risk, i.e., potential for erosion in price levels. Therefore, the investors who are somewhat risk-averse would zero in on 110 and 114 areas, avoiding perhaps the rest of the county. Conversely, the investors specializing in distressed portfolios in high risk areas would factor in high risk premiums while pricing out their portfolios, particularly when dealing with the cash-strapped developers needing to raise cash to stay afloat. Even within a leading-3 Zip, the risk spread could be fairly wide so the investors should further narrow their choices down as they decide to dig deeper.

Of course, investors, depending on their investment philosophy and parameters, have different definitions of risk. Therefore, some investors would consider my risk definitions quite appropriate, while others would redefine them in accordance with their specific requirements. Nonetheless, the fact remains, the geographic price-income ratio analysis is one of the easiest and most meaningful tools investors possess to assess the macro investment risk before entering into a new market. It should also be part and parcel of their opportunity cost analysis while evaluating a set of mutually exclusive (competing) markets.

Again, my objective here is to show how to use this simple tool to get a bird’s eye view of the potential market risk, rather than highlighting risks Queens market currently poses. I just happened to have easy access to the Queens sales and income data, the accuracy of which I have not verified.

Thanks,

Sid Som

Data sources:
Sales: NYC Department of Finance website
Income: Microsoft MapPoint 2009 (North America)

Health of Commercial Real Estate Loans

2009-11-15T12:35:00.010-05:00

While there are hosts of data sources to evaluate commercial real estate in the US, the most reliable data and analyses, unquestionably, are contained in the quarterly publication titled ‘Charge-off and Delinquency Rates on Loans and Leases at Commercial Banks’ from the Federal Reserve. The publication contains the two most important macro metrics – Charge-off rate and Delinquency rate – that are central to the understanding of the health of commercial real estate loans. To make matters easier, the publication even breaks the results down between all commercial banks and the largest 100 banks making and carrying such loans.

To understand the difference between the charge-off rate and delinquency rate as well as the banks in question, let’s zero in on the definitions as offered by the Federal Reserve:

“Charge-offs, which are the value of loans removed from the books and charged against loss reserves, are measured net of recoveries as a percentage of average loans and annualized.”
“Delinquent loans are those past due thirty days or more and still accruing interest as well as those in nonaccrual status. They are measured as a percentage of end-of-period loans.”
“Banks are insured U.S.-chartered commercial banks. Size, where used, is measured by consolidated assets adjusted for mergers; where used, other banks (ignored in this article) are those smaller than the 100 largest.”

Simply put, the charge-off rate is historical while the delinquency rate is ongoing. Therefore, they are mutually exclusive. The combined rate is naturally more consequential in depicting the total picture. On a related note, the correlation between the two is .90, a near perfect collinearity, and therefore almost predictive of each other.

The following table and the chart will demonstrate how the health of the commercial real estate in the US is becoming increasingly anemic, thus preventing the economy from recovering from its current misery and perhaps pushing it back to a double-dip.

(click on the image to get an enhanced view)

The combined charge-off and delinquency rate has jumped from 1.55% in 2007-Q1 to 10.15% in 2009-Q2 – an astonishing 555% spike. The picture is virtually unchanged between all commercial banks and the largest 100. At this rate, by the end of next year, the commercial real estate industry may easily experience a jaw-dropping combined rate ranging somewhere between15% and 18%, depending on the level and pace of unfreezing of the credit market and the reopening of its CMBS counterpart. Of course, the current charge-off rate is still under 2.5%, but going forward it will rise at a much faster pace as a result of the current exponential growth in delinquencies.

As we all know, the very existence of the commercial real estate industry largely depends on the availability of financing. During the recent credit bubble, those who were able to finance their properties with minimum skin in the game would be out of luck now if confronted with a balloon falling due. Therefore, the properties/owners requiring refinancing are considered more or less distressed. Case in point: A flagship Boston office property was recently auctioned off at fifty percent of its prior sale price. The point is, the conventional valuation metrics like rental rates, vacancy rates, expense ratios and cap rates would hardly matter if the need for an immediate financing is on the table. Unfortunately, even if the banks are willing to refinance, the new appraisal may push the LTV to a point the deal would be untenable.

At the municipal finance level, the assessors should seriously research and consider the availability of financing to reduce exposure to their municipal budgets. For example, if the current median LTV in their local market is down to 60% from the prior 80%, the cap rate may by increased by two percentage points. While lowering the value of the properties on the roll does not generally translate to lower revenue (in fact, target revenue is a function of tax rates), it nonetheless reduces the budget exposure and, in turn, the future refund liability.

(click on the image to get an enhanced view)

The above chart clearly shows how the commercial lending fell off the cliff. From a net lending of $1.7T in 2008-Q3 banks reverted to a net borrowing in 2009, primarily by tapping into the TARP money as well as other short-term credit windows offered by the Fed. This reversal virtually forced most commercial banks to preserve their capital ratios and in the process they either stopped making such loans or tightened their lending standards to the extent that most potential borrowers failed to put any deals together. The bridge loans are also very few and far between, adding to the misery.

Randall Zisler, chief executive officer of Zisler Capital Partners LLC, in a recent report titled “A crisis of unprecedented proportions is approaching” estimated that building owners may default on $500 billion to $750 billion of mortgage debt – as much as 54 percent of the $1.4 trillion in loans coming due in four years. The report added, “Much of the debt is likely worth about 50 percent of par, or less. Many banks will end up insolvent as they reduce the value of their holdings.”

Meanwhile, a new breed of investors and hedge funds are beginning to invest in distressed commercial real estates which will add some liquidity to the market and hopefully attract others as well.

Thanks,

Sid Som

Data source:
http://www.federalreserve.gov/econresdata/releases/statisticsdata.htm

Florida's Housing Boom and Bust

2009-10-03T10:18:00.011-04:00

Americans’ love affair with Florida is well-known. Florida's two major housing markets – Miami and Tampa according to the Case-Shiller tracking – have seen the same boom and bust in recent years as most of the other major markets in the US.

Miami’s condo market, in particular, has also been a hot target for the speculative investors, enticing builders to invest heavily in that market segment until the inevitable struck. In the 80’s, Tampa was the rising star as a tech center. However, after the dot com bust, as a vast majority of those centers were moved to cheaper overseas locations as well as a big slice of the remaining jobs were later outsourced, the housing demand started to wane creating not only a glut but bringing the prices drastically down.

(click on the graph to get an enhanced view)

Between Jan-03 and Jul-06, the Miami price index jumped 94% (143.78 to 278.33), Tampa rose 79% (133.22 to 238.09), while the composite for the top-10 US markets climbed a much lower 58% (142.86 to 226.17). During those frenzy years, prices in most of the coastal markets ascended rapidly outpacing the growth in personal and household incomes. But the major Florida markets apparently stayed way ahead of the curve, naturally setting them up for a greater collapse. Let the statistics speak for themselves: since Jul-06 to Jul-09 (the most recent Case-Shiller indices available as of this writing), Miami index has now come down to 147.27, while Tampa at 142.84, and the top-10 US at 155.85. In other words, these major Florida markets, along with the top-10 composite, are now back down to the early-to-mid 2003 price levels. Just the way the Miami prices galloped ahead of the other markets, it took the lead on the way down as well.

(click on the graph to get an enhanced view)

While the high R-squared (.9877) between the two local indices demonstrates that the markets moved in tandem (on the way up as well as down), the angle of the regression line however clearly shows Miami had a higher beta.

Unfortunately, the folks who bought in 2004-08 are underwater – those who bought in mid-2006 are obviously the worst-hit. While the government programs (including the $8,000 first-time homebuyer’s credit) are working to some extent, the available inventory is still so huge that it can take several years before some sort of balance returns to the market. Meanwhile, a big chunk of the remaining speculators and the recession victims will add to the glut, preventing the inventory situation to improve any time soon.

Related to the last housing and credit bubble, some statistics show FHA is now contributing to almost 45% of all originations, thus transferring the sub-prime originations from the private to the public sector. FYI, here are some of the FHA mortgage requirements:

• 3.5% down payment requirement;
• Bankruptcy must be at least two years old, with good credit since;
• Foreclosure must be at least three years old, with good credit since.

Since the Federal government has essentially taken over the sub-prime originations, at least we won’t have to blame the banks as the next major bubble begins to gain ground.

Thanks,

Sid Som

Where is Queens housing market headed?

2009-08-20T22:09:00.021-04:00

Like most other major housing markets in the country, the Queens, NY housing market has also been trending down. The tightening of the lending standards – higher FICO scores, larger down payments and a near complete removal of the sub-prime and Alt-A mortgages – has contributed significantly to the downward spiral of home prices. Worse yet, the Jumbo loans which tend to buoy the resale markets of the affluent neighborhoods are nowadays much harder to come by, making those markets even harder hit. The overall situation may be further aggravated once the $8,000 home buyers credit expires in November.

Simply put, we are down to only old-fashioned prime mortgages, thereby perceptibly shrinking the overall resale market and reducing the number of available sales. According to the July MLS report, the month’s supply for Queens now stands at 12 – a glut that is going to impact any immediate prospect of prices bottoming out, let alone any talk of recovery or upswing.

In a market where the median sale price is still $430,000, the availability of financing is the key, without which prices would continue to dwindle down. No doubt it is not going to be a linear decline, meaning some pauses and limited bounces will take place even on the way down, but the general trend will be downward until the flow of financing returns to some level of normalcy, including the Jumbo market. If the flow returns to the conforming market without significant easing on the Jumbo side, we will gradually see a bimodal distribution in the market, further dampening the higher end of the value curve.

Let’s take a look at the following price trend chart. Whether we study the movement by absolute prices or normalized by the building size, we see a fairly similar picture in terms of the decline in prices (-11% either way). The slight flattening of the curve between Q1 and Q2 is the seasonality. As we all know, residential real estate could be highly seasonal and therefore de-seasonalized comparisons (for example, 2008-Q2 vs. 2009-Q2) are real apples-to-apples comparisons.

Quarter/Sale Price/SPSF
2008-Q3/$480,500/$299
2008-Q4/$465,000/$290
2009-Q1/$420,785/$266
2009-Q2/$430,000/$266

Of course, there are other granular ways to look at the housing market. Let’s zero in on the two most common ways: by house size and by house age. For this analysis, I have created two sub-categories – below the median and above the median. According to the sales sample, the median house size in Queens is 1,568 SF, while the median year built is 1935, translating to a median age of 74 (i.e., 2009 – 1935). Now, let’s take a look at the following matrix to identify any trend (considering only two sub-categories, the median values are included in 'Below the median'):

House Size
Below the median
2008-Q3/$420,000//2009-Q2/$385,000
Above the median
2008-Q3/$565,000//2009-Q2/$500,000

House Age
Below the median
2008-Q3/$432,000//2009-Q2/$380,000
Above the median
2008-Q3/$550,000//2009-Q2/$418,000

Again, the trend is obvious – falling prices. As expected, due to the builder closeouts, the sharpest decline is in the new home category. In a downturn as severe as this, builders tend to stay afloat by pushing the inventory out as fast as they reasonably can.

Another major headwind that is plaguing Queens is fast-rising unemployment. In one year, the unemployment rose from 5.2% to 8.5% - an astounding 330 basis point jump (table below), severely impacting the housing market and thereby bringing the median down from $485,000 to $415,000. Of late, while there has been an expected seasonal rise in prices, the correlation coefficient between the monthly median sale prices and unemployment rates is -.80 (as you know, the correlation coefficient varies between -/+1, where -1 is the perfectly negative correlation between two variables). In fact, without the recent two seasonally up months, the coefficient is -0.90, hinting again at the future correlation as we come out of the seasonally high summer months and other government supports and mandates are gradually withdrawn or relaxed. Late next year, as the housing market begins to bottom out and makes a sideways movement, this coefficient will significantly retreat from these elevated levels. Of course, in the next two to three quarters, the median price may easily fall another 10% - 15% as unemployment spikes closer to 10%.

Data Sources:
Sales - NYC Department of Finance
Unemployment - NYS Department of Labor

Thanks,

Sid Som