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Forward Modeling:
Knowing Tomorrow’s Housing
      Market Today
              July 2, 2011


            Scott Sambucci
    Vice President, Market Analytics
       scott@altosresearch.com
             (415) 931 7942
Research Question
• How to develop a housing market
  forecasting model applicable to more
  than 20,000 zip codes across property
  types and price quartiles?

• How to enable regular model revision
  and updates as new information and
  data becomes available?
Active Market signals future transaction
price
           Home listed
             $429,000                                                   Buyer financing fails,
           Inventory 49         Neighbor home                             Property relisted
                                     listed                                   $394,000
                                   $409,000
                                                                                  Deal closed
                                                                                   $389,000
                                          Price reduced
                                             $398,000
                                           Inventory 69
                                                                                                 Transaction
                                                           Offer made
                                                                                                  Recorded
                                                            $391,000




   March                  May            July             Sept          Nov             Jan


                  Closed transaction = 1 data point, months too late
   Active Market = 9 months of pricing, price changes, supply and demand, leading
                                       indicators
Sample Sizes: Transactions vs. Actives
Lead the Headlines by 3 months
Housing Market News: Release &
Report Dates
                        Source                            Inflection Date   Data Published
           Altos Research Q3-2010 Webcast                                       Jul-10
                                                            14-Jan-11         17-Jan-11

 Altos 20-city Composite Price of New Listings (weekly)
     Altos 20-city Composite Median Price (weekly)           4-Feb-11          7-Feb-11

         Altos 20-city Composite Median Price               25-Mar-11         28-Mar-11
                  (90 Day Rolling Avg)

                    CoreLogic HPI                             Apr-11           1-Jun-11

           FHFA national home price index                     Apr-11          22-Jun-11

                   Radar Logic RPX                            Apr-11          23-Jun-11

          S&P Case Shiller 20 City Composite                  Apr-11          28-Jun-11
Importance of Active Market Indicators

•   ANGLIN, RUTHERFORD & SPRINGER (2003), “The Trade-Off Between
    the Selling Price of Residential Properties and Time-on-the-Market: The
    Impact of Price Setting,” JJREFE
•   MILLER & SKLARZ (1987), “Pricing Strategies and Residential Property
    Selling Strategies,” JRER
•   SPRINGER(1996), “Single-family housing transactions: Seller
    motivations, price, and marketing time,” JREFE
•   YAVAS & YANG (1995), “The Strategic Role of Listing Price in
    Marketing Real Estate: Theory and Evidence,” REE
•   KANG & GARDNER (1989), “Selling Price and Marketing Time in the
    Residential Real Estate Market,” JRER
Published research & models limited by
local data sets & time series

•   Boston: GENESOVE & MAYER (2001). “Loss Aversion and Seller
    Behavior: Evidence from the Housing Market,” QJE
•   Stockton, CA: KNIGHT (2002), “Listing Price, Time on Market, and
    Ultimate Selling Price: Causes and Effects of Listing Price Changes,”
    REE
•   Arlington, TX: ANGLIN, RUTHERFORD, & SPRINGER (2003), “The Trade-
    Off Between the Selling Price of Residential Properties and Time-on-
    the-Market: The Impact of Price Setting,” JREFE
•   Columbus, OH: HAURIN, et al (2006), “List Prices, Sale Prices, and
    Marketing Time: An Application to U.S. Housing Markets,” Working
    Paper
The Data

• 400 individual statistics & leading
  indicators updated weekly for 20,000 zip
  codes based on the active market
• Independently calculated by property
  type (single-family & condo) and price
  range quartile
• Primary data with uniform methodology
  for all statistics
Model Development
Step 1: Traditional OLS
Objective:         Build models by zip code for 20k zips
Process:           Test set  Limited OLS Models
Outcome:           Variables & coefficients changed drastically from
                   market to market

Step 2: Regression Trees (CART)
Objective:        Increase accuracy from OLS
Process:          Test set  Built models for 20k zips
Outcome:          No coefficients, Trees randomly generated,
                  Interpretability problems

Step 3: Least Angle Regression (LARS)
Objective:        Increased transparency
Process:          Test set  Build models for 20k zips
Result:           Linear model with Coefficients, Transparent, Interpretable
What’s next?

• Introduce non-linearity
  – Add quadratic basis functions to capture
    economic growth
• Introduce related variables
  – Mortgage rates
  – Macroeconomic indicators
  – Rental rates
  – REO/Distressed market-specific
Contact
Scott Sambucci
Vice President, Market Analytics
(415) 931 7942
scott@altosresearch.com
@scottsambucci
www.altosresearch.com
blog.altosresearch.com

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Western Economics Association - Forward Valuation Model (Altos Research)

  • 1. Forward Modeling: Knowing Tomorrow’s Housing Market Today July 2, 2011 Scott Sambucci Vice President, Market Analytics scott@altosresearch.com (415) 931 7942
  • 2. Research Question • How to develop a housing market forecasting model applicable to more than 20,000 zip codes across property types and price quartiles? • How to enable regular model revision and updates as new information and data becomes available?
  • 3. Active Market signals future transaction price Home listed $429,000 Buyer financing fails, Inventory 49 Neighbor home Property relisted listed $394,000 $409,000 Deal closed $389,000 Price reduced $398,000 Inventory 69 Transaction Offer made Recorded $391,000 March May July Sept Nov Jan Closed transaction = 1 data point, months too late Active Market = 9 months of pricing, price changes, supply and demand, leading indicators
  • 5. Lead the Headlines by 3 months
  • 6. Housing Market News: Release & Report Dates Source Inflection Date Data Published Altos Research Q3-2010 Webcast Jul-10 14-Jan-11 17-Jan-11 Altos 20-city Composite Price of New Listings (weekly) Altos 20-city Composite Median Price (weekly) 4-Feb-11 7-Feb-11 Altos 20-city Composite Median Price 25-Mar-11 28-Mar-11 (90 Day Rolling Avg) CoreLogic HPI Apr-11 1-Jun-11 FHFA national home price index Apr-11 22-Jun-11 Radar Logic RPX Apr-11 23-Jun-11 S&P Case Shiller 20 City Composite Apr-11 28-Jun-11
  • 7. Importance of Active Market Indicators • ANGLIN, RUTHERFORD & SPRINGER (2003), “The Trade-Off Between the Selling Price of Residential Properties and Time-on-the-Market: The Impact of Price Setting,” JJREFE • MILLER & SKLARZ (1987), “Pricing Strategies and Residential Property Selling Strategies,” JRER • SPRINGER(1996), “Single-family housing transactions: Seller motivations, price, and marketing time,” JREFE • YAVAS & YANG (1995), “The Strategic Role of Listing Price in Marketing Real Estate: Theory and Evidence,” REE • KANG & GARDNER (1989), “Selling Price and Marketing Time in the Residential Real Estate Market,” JRER
  • 8. Published research & models limited by local data sets & time series • Boston: GENESOVE & MAYER (2001). “Loss Aversion and Seller Behavior: Evidence from the Housing Market,” QJE • Stockton, CA: KNIGHT (2002), “Listing Price, Time on Market, and Ultimate Selling Price: Causes and Effects of Listing Price Changes,” REE • Arlington, TX: ANGLIN, RUTHERFORD, & SPRINGER (2003), “The Trade- Off Between the Selling Price of Residential Properties and Time-on- the-Market: The Impact of Price Setting,” JREFE • Columbus, OH: HAURIN, et al (2006), “List Prices, Sale Prices, and Marketing Time: An Application to U.S. Housing Markets,” Working Paper
  • 9. The Data • 400 individual statistics & leading indicators updated weekly for 20,000 zip codes based on the active market • Independently calculated by property type (single-family & condo) and price range quartile • Primary data with uniform methodology for all statistics
  • 10. Model Development Step 1: Traditional OLS Objective: Build models by zip code for 20k zips Process: Test set  Limited OLS Models Outcome: Variables & coefficients changed drastically from market to market Step 2: Regression Trees (CART) Objective: Increase accuracy from OLS Process: Test set  Built models for 20k zips Outcome: No coefficients, Trees randomly generated, Interpretability problems Step 3: Least Angle Regression (LARS) Objective: Increased transparency Process: Test set  Build models for 20k zips Result: Linear model with Coefficients, Transparent, Interpretable
  • 11. What’s next? • Introduce non-linearity – Add quadratic basis functions to capture economic growth • Introduce related variables – Mortgage rates – Macroeconomic indicators – Rental rates – REO/Distressed market-specific
  • 12. Contact Scott Sambucci Vice President, Market Analytics (415) 931 7942 scott@altosresearch.com @scottsambucci www.altosresearch.com blog.altosresearch.com