111111
`
`1111111111111111111111111111111111111111111111111111111111111111111111111111
`US 20020087389Al
`
`(19) United States
`(12) Patent Application Publication
`Sklarz et ai.
`
`(10) Pub. No.: US 2002/0087389 Al
`J ul. 4, 2002
`(43) Pub. Date:
`
`(54) VALUE YOUR HOME
`
`Publication Classification
`
`(76)
`
`Inventors: Michael Sklarz, Honolulu, HI (US);
`John R. Willey JR., Honolulu, HI (US)
`
`(51)
`Int. CI? ..................................................... G06F 17/60
`(52) U.S. CI. ................................................................ 705/10
`
`Correspondence Address:
`GEORGE E. DARBY
`P.O. BOX 893010
`MILILANI, HI 96789-3010 (US)
`
`(21) Appl. No.:
`
`09/942,415
`
`(22) Filed:
`
`Aug. 28, 2001
`
`Related U.S. Application Data
`
`(63) Non-provisional of provisional application No.
`60/228,899, filed on Aug. 28, 2000.
`
`(57)
`
`ABSTRACT
`
`The Value Your Home invention collects real estate, and real
`estate related, data from various sources, adjusts and filters
`the data, processes that data using trend analysis, compa(cid:173)
`rable market analysis, buy/sell signal analysis, and appraisal
`engines, responds to user inputs, and provides information
`outputs and trend, comparable market analysis, buy/sell
`signal, and appraisal decision tools to users.
`
`104-~
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`~102
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`Internet
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`
`VYH App Server
`
`\107
`
`User n
`
`110J
`
`VYH Web Server
`
`

`

`Patent Application Publication
`
`Jui. 4, 2002 Sheet I of 27
`
`US 2002/0087389 Al
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`[jig. 3
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`DEFINE YOUR QUERY
`
`This is the first of two pages on which you define a query that will be used to produce trend graphs. Define
`your query using City/Zip or Address Proximitv Criteria and click on the continue button for the selected
`method.
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`Query by State/County/City-Zip
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`State
`/CALIFORNIA
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`County
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`ALBANY 94706
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`State
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`IALAMEDA I
`City-Zip
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`(ALAMEDA 945011
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`Minimum
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`
`!Jig. 5
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`Select Graphs To Produce:
`
`Price
`Price/Bedrm
`Price/Sq Ft
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`Select All
`
`Deselect All
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`Clear All Fields
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`Sold-Volume & Average-Price
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`700 _,
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`- - t1 olum.e - - Price
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`- - Best Fit Line(Price)
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`SAN DIEGO COUNTY, CALIFORNIA
`City-Zip: LA JOLLA 92037
`Property Type: Single Family Bedroom: All Bathroom: All
`Sale Type: Resale, New
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`SAN DIEGO COUNTY, CALIFORNIA
`City-Zip: LA JOLLA 92037
`Property Type: Single Family Bedroom: All Bathroom: All
`Sale Type: Resale, New
`
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`

`

`Patent Application Publication
`
`Jui. 4, 2002 Sheet 11 of 27 US 2002/0087389 Al
`
`

`

`OEF It~E YOU R. QU ERY
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`
`

`

`Address: 24232 CHRISANTA, MISSION VIEJO, CA 92691
`
`Property Type [Singl~-F5mily I
`
`F or Specific Comparables Select Properties
`
`r. Within I ' Miles of Property
`r Within I ' Addresses Above & Below
`
`State
`
`'CALIFORNIA
`
`County
`
`IORANGE
`
`City-Zip
`I MISSION VIEJO 926911
`
`Re·select Areals)
`
`Query Help
`
`fiUJ·13
`
`Clear Arr Fields
`
`Produce Graphs
`
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`

`!}ifJ·14
`
`Sort BylSold P'ice-3
`
`Comparison Summary:
`
`Sold
`Price
`
`Bed
`
`Bath
`
`U ... ing Area
`Sq Ft
`
`land Area
`Sq Ft
`
`Minirn.Jm
`
`$260,000
`
`Maximum
`
`$330,000
`
`2
`
`4
`
`Average
`
`$304,167
`
`3.2
`
`2.0
`
`2.0
`
`2.0
`
`1,360
`
`2,100
`
`1,497
`
`6,000
`
`8,400
`
`7,592
`
`ILppx
`Age
`
`33
`
`34
`
`33.3
`
`Produce Comp9.ratles
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`

`

`CLOSEST PROPERTIES SELECTED
`
`Description of Property:
`
`24232 CHRISANTA, MISSION VIEJO, CA92691 Single-Family
`Estimated Price $282,500; 3 Bd; 2 Bth; Living 1 ,320; Land 7,000; Age 34
`
`Predicted Value $282,993
`
`!Jig. IS
`
`For the Period 2/112001 To 812612001 - 6 Properties Selected
`In the column marked "X", below, click the checkbox associated to each of (up to) 6 properties for which
`you would like to produce addtional comparable analysis, then click the Produce Comparab/es button,
`below
`
`Address
`
`Zip
`
`Date
`
`DR
`
`MISSION
`VIEJO
`
`I sold I sold r-~~[L:;.;d~r-
`r-I
`Price I Bed I Bath I Are'; I Al'\E!!a I Age I Pool
`I x
`92691·
`1313012001 1$260.000 13~11.3OO17.240 f34rN
`I P' /24191 1 BARGWERO
`4102
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`rrl260051 COR~~ENTE ~~:~~N I 9!~~. 1212712001/$297.000 r-FFls.400 f33jN
`M~7:.:gN 1 9:~~. 14f.24f.2001 1$306.000 ~FFIS.400 f33~
`1 P' 1263251 TARRASA L.N
`rrl26362 1 PACATO DR
`g!~~~. 13126120011$314.000 r-FFI7.840 f33~
`~7:~~N
`9!~~~. 14f.24f.2001 1$318.000 r-FFI7.665 f33jN'
`1 P' 124261 1 BAR~~ERO
`rrl261011 CORD~~L.ERA ~~:~~N 1 9!~~. 12/15120011$330.000 ~FFI6.000 Fr-
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`

`COMPARABLE MARKET ANAL VSIS
`Prepared on August 26, 2001
`
`flUj.16
`
`Description of Property:
`
`24232 CHRISANTA , MISSION VIEJO, CA 92691
`
`Estimated Price: $282,500
`Number of Bedrooms: 3
`Number of Bathrooms: 2
`Living Area Sq. Ft.: 1,320
`Land Area Sq. Ft.: 7,000
`Approximate Age: 34
`Property Type: Single-Family
`Within .25 Miles of
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`MISSION VIEJO ZIP 92691 SINGLE-FAMILY
`SOLD PRICE VS. LIVING AREA (2101-8101)
`$600,000.,..., - - - - - - - - - - - - - - .
`•
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`Patent Application Publication
`
`Jui. 4, 2002 Sheet 18 of 27 US 2002/0087389 Al
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`MISSION VIEJO ZIP 92691 SINGLE-F MIlLY PRICE PER
`SQUARE FOOT OF LIVING AREA DISlRIBlITION (2101-1101)
`60 · , , - - - - - - - - - - - - - - - - - ,
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`Patent Application Publication
`
`Jui. 4, 2002 Sheet 20 of 27 US 2002/0087389 Al
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`Patent Application Publication
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`Jui. 4, 2002 Sheet 21 of 27 US 2002/0087389 Al
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`MISSION VIEJO ZIP 92691 SINGLE-F AM:IL Y
`BEDROOM DIS1R.IBUTION (2/01-8/01)
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`Patent Application Publication
`
`Jui. 4, 2002 Sheet 23 of 27 US 2002/0087389 Al
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`

`Description of Property:
`
`ESTIMATED MARKET VALUE
`
`24232 CHRISANTA, MISSION VIEJO, CA92691 Single-Family
`Estimated Price $282,500; 3 Bd; 2 Bth; Living 1,320; Land 7,000; Age 34
`Using our proprietary calculations, the predicted price for this property, based on the sold properties
`selected is: $282,993
`
`SOLD SUMMARY STATISTICS (AVERAGES)
`
`For the Period 2/112001 To 812612001 166 Properties Selected
`
`Ci'l:y
`MISSION VIEJO. CA
`92691
`
`$326.629
`
`3.4
`
`2.3
`
`27.9
`
`Uving
`A .... a Sq Ft:
`1.786
`
`Land A .... a
`Sq Ft
`6.824
`
`Uving
`Price / Sq Ft:
`$182.83
`
`Land
`Price/Sq Ft:
`$47.94
`
`The property you have described compares to the averages of the comparable properties selected as
`follows:
`
`Your E8timated Price of
`Your Living Price/SqFt of
`Your Land Price/SqFt of
`
`$282,500
`$214.02
`$40.36
`
`is
`is
`is
`
`$44,029 or 13.48% below average
`$31.19 or 17.06% above average
`$7.59 or 15.82% below average
`
`Property Attribute Comparison Table in Percent
`
`Properties .... ith greater
`
`-#
`-#
`Price Oednns Baths
`72.89
`36.76
`37.95
`
`Age
`
`5.42
`
`Properties .... ith lesser
`
`27.11
`
`7.23
`
`6.02
`
`87.95
`
`----"""'pertie~with equa~ .00
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`
`.. -
`
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`6.63
`56.02
`- - - - - - - -
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`81.93
`
`16.26
`
`1.81
`
`Land
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`43.37
`
`64.82
`
`1.81
`
`Land
`Uving
`Price!SqF1: Price/SqFt:
`27.71
`73.49
`
`72.29
`
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`

`gig. 27
`
`SAN DIEGO HOME PRICE INDEX & LA JOLLA AVERAGE PRICE (1989=100)
`
`180 .-------------------------------------------------------------------------~
`
`170 -I------~--
`
`160
`
`150
`
`- -.. - SAN DIEGO HPI
`•
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`

`

`US 2002/0087389 Al
`
`Jul. 4, 2002
`
`1
`
`VALUE YOUR HOME
`
`RELATED APPLICATIONS
`
`[0001] This application claims the benefit of the provi(cid:173)
`sional patent application, Ser. No. 60/228,899, filed on Aug.
`28, 2000, in the U.S. Patent and Trademark Office for an
`invention entitled "Value Your Home".
`
`BACKGROUND OF THE INVENTION
`
`[0002] 1. Field of the Invention
`
`[0003] This invention relates generally to the delivery of
`real estate sales price information, identification and com(cid:173)
`parisons of comparable real properties, and sales price
`predictions. In particular, the invention relates to Web-based
`services for providing historical real estate sales informa(cid:173)
`tion, trend analysis, comparable market analysis, buy/sell
`signals, and individually tailored appraisals. The term
`"appraisal" means herein an estimated appraisal (predicted
`sales price), as opposed to a formal appraisal prepared by a
`certified or licensed appraiser.
`
`[0004] 2. Description of Related Art
`
`[0005] Real estate market information is important to
`home buyers and sellers, real estate brokerages and agents,
`home builders, appraisers, financial institutions that use real
`estate as collateral to secure loans, mortgage and title
`insurance companies, and government housing finance
`agencies. At present, there are approximately 600,000 real
`estate agents servicing annual sales of approximately 5
`million existing homes and of 800,000 new homes. In
`addition to the real estate businesses involved, a buyer and
`a seller involved in each transaction constitute approxi(cid:173)
`mately 11 million additional potential customers for resi(cid:173)
`dential real estate information services.
`
`[0006] Attempts have been made to improve the provision
`of real estate information. These efforts have been focused
`primarily on the residential real estate market. U.S. Pat. No.
`5,636,117 to Rothstein describes a method for generating
`real estate market indices for use in a real estate information
`service. U.S. Pat. No. 5,361,201 to lost, et aI., describes a
`modeling process that predicts real estate sales prices and
`trends, and that can use neural networks to better accom(cid:173)
`modate non-linearities in market data. These patents predate
`the World Wide Web and lack interactivity.
`
`[0007] Sales price prediction is essentially synonymous
`with valuation. Sales price prediction can rely on many types
`of valuation methodologies, but the most common types are
`comparable market analysis and trend analysis. "Compa(cid:173)
`rable market analysis" predicts a sale price based on actual
`("historic") sales prices of similar properties, where "simi(cid:173)
`lar" has a range of meanings. "Similar" can include a
`geographic area surrounding a subject property, or neigh(cid:173)
`borhoods with similar attributes located elsewhere in the
`city, state, nation, or geographic radius. "Similar" can also
`include physical attributes of a structure, e.g., number of
`bedrooms, total living area, swimming pool area, number of
`parking spaces, etc. "Similar" can further include proximity
`to certain types of infrastructure, e.g., K-12 schools, univer(cid:173)
`sities, public parks, freeway interchanges, libraries, etc.
`"Trend analysis" predicts the sales price of a property by
`applying algorithms, usually multiple regression algorithms,
`to historical times series data. The most common trend
`analysis uses a Least Squares Deviation algorithm.
`
`[0008] A predicted sales price is in itself a decision tool,
`but the predicted sales price has been used in the securities
`industry as an input to additional decision tools, such as
`buy/sell signals. A buy/sell signal is typically generated
`when certain statistical conditions are satisfied. In a basic
`approach, buy/sell analysis could generate a sell signal if
`trend analysis output indicated a predicted sales price maxi(cid:173)
`mum for a given type of property had been reached. More
`advanced buy/sell signals, known in the art of securities
`trading, compare different two or more trend lines based on
`different types of moving averages, use adjustments and
`filtering of input data, and select different types of input data
`depending upon the type decision tool.
`
`[0009] Trend information is of particular importance when
`zoning, infrastructure, employment, and other external fac(cid:173)
`tors are changing or have recently changed. Buy/sell signals,
`while known in the securities trading art, are rare or absent
`in the real property industry. One major problem confound(cid:173)
`ing efforts to provide improved real property transaction
`information and decision tools has been inconsistencies in
`the types of data collected about properties in different cities,
`counties, or other political subdivisions. For example, there
`are hundreds of different types of database fields used to
`describe residential properties in multiple listing service
`database. Moreover, the types of database fields are often not
`consistent among multiple listing services covering proper(cid:173)
`ties in a single city, much less across a broader area. A
`second problem has been the lack of analytic tools tailored
`to real property transaction information. Analytic tools
`developed in the art of securities trading, such as trend
`analysis and buy/sell signals for securities, cannot easily be
`adapted for the real estate industry since the securities
`trading analytic tools depend on only a few data types,
`typically name of the stock or bond, date, sales price, and
`volume. As noted above, hundreds of different data types are
`used in real estate, which means that tools developed for
`securities transactions are grossly inaccurate when applied
`to real property transactions.
`
`[0010] To further complicate the problem of improving
`real property transaction information and decision tools,
`there are many types of users of transaction information and
`tools. Among such users are buyers and sellers of properties;
`real estate brokers and brokerages; mortgage lenders; mort(cid:173)
`gage brokers; mortgage-backed securities issuers; construc(cid:173)
`tion companies, home owner services (e.g., landscaping,
`termite testing, interior design, furnishings); commercial
`owner services (e.g., carpeting, space layout, interior design,
`furnishings, janitorial); industrial owner services (e.g., waste
`disposal, space layout, logistics, equipment, janitorial); and
`insurance companies (e.g., title, fire and casualty, personal
`injury, mortgage). These users are found in one, two, or all
`of the traditional sectors of the real estate industry: residen(cid:173)
`tial, commercial, and industrial.
`
`[0011] The identity of the problems causing inaccuracies
`in analytic tools for the real estate industry, and the delivery
`of transaction information and access to such tools, has been
`sought by practitioners in the art without success. Efforts to
`improve transaction information and decision tools for the
`residential property sector of the real estate industry have
`been particularly disappointing, particularly in view of the
`inter activity, affordability, and ease of access to information
`and analytic tools provided by the World Wide Web in
`industries other than real estate.
`
`

`

`US 2002/0087389 Al
`
`Jul. 4, 2002
`
`2
`
`[0012] Today, there are some Websites, such as real(cid:173)
`estate.yahoo.com and iown.com, that enable a home seller to
`obtain recent sales prices. Some Websites, e.g., those at
`www.freddiemac.com and www.homegain.com, generate
`sales price predictions (valuations) that have a limited
`number of input variables and, consequentially, wide mar(cid:173)
`gins of error. Current Websites typically do not provide
`decision tools such as comparable market analyses, trend
`analysis, and buy/sell signals for real estate properties,
`especially combined with flexible query tools. There is
`unmet demand for improved real property transaction infor(cid:173)
`mation and decision tools, particularly for residential prop(cid:173)
`erties.
`
`SUMMARY OF THE INVENTION
`
`[0013] The inventors of the VYH invention identified the
`primary problems in the poor performance of existing real
`estate valuation services, including automated valuation
`services and valuation tools on Websites, as poor filtering
`and adjustment of raw data, a lack of data type mapping, a
`lack of flexibility in a user's selection of property attributes
`with which to generate an comparable market analysis,
`appraisal, or other decision tool, and a lack of sophistication
`in the algorithms used in the software engines generating a
`trend analysis, comparable market analysis, buy/sell signal,
`or appraisal. The VYH invention embodies solutions to
`those problems, and the preferred embodiment is directed
`toward residential property sales transactions. The VYH
`invention is an computerized real estate information system,
`and the best mode is the online system and method described
`herein. The scope of the invention, however, includes dis(cid:173)
`tribution of the output of the VYH system not only online
`(over a private network. over the World Wide Web, etc.), but
`publication of the output in other media, such as audio text,
`printed publications, and video recordings.
`
`[0014] The Value Your Home invention provides historical
`real estate sales information, trend analysis, comparable
`market analysis, buy/sell signals, and individually tailored
`appraisals (sales price predictions), using methods that sig(cid:173)
`nificantly improve the accuracy, speed, afford ability, and
`delivery of such information. The Value Your Home
`("VYH") invention sources data via a data bus or data
`communications network (e.g., the Internet) from one or
`more local and/or remote sources, e.g., Multiple Listing
`Services ("MLS"), real property tax records, geographic
`information services ("GIS"), etc., processes that informa(cid:173)
`tion using at least one software engine, and provides infor(cid:173)
`mation outputs and decision tools to users, including without
`limitation persons using Web browsers connected to the
`invention via a data communications network such as the
`Internet. The information outputs and decision tools are
`preferably contained in one or more display windows that
`the user navigates using scroll bars, buttons, and other
`navigation techniques known in the art. "User" means a
`natural person, or end-user, but also includes a process
`running on a computer that accept the information output of
`the invention for further processing.
`
`[0015] The principal information outputs are: Historical
`Price Charts, Historical Price Charts-Query By Address
`Proximity, Geographical Information System ("GIS") Map(cid:173)
`ping/Market Maps, Price Distribution Charts, Historical
`Mortgage Charts, Technical Analysis of Historical Home
`Price Series, Fundamental Analysis of Historical Home
`
`Price Series, Comparable Market Analysis, and Appraisals.
`The Technical Analysis of Historical Home Price Series and
`Fundamental Analysis of Historical Home Price Series
`information outputs include Trend Analysis and Buy/Sell
`Signals. The Appraisal information output includes a sales
`price prediction, also known as a valuation, for a subject
`property.
`
`[0016] The output information is generated by the inven(cid:173)
`tion in response to queries formulated by users. Queries are
`formulated using drop-down menus and item selection, and
`by entry of free text in text dialog boxes, on a user interface.
`The user interface provides display of information outputs
`and decision tool outputs, entry of queries, and navigation
`within the VYH service. The preferred embodiment uses a
`Web browser as the user interface. The Web brows