US2013262284A1PendingUtilityA1

Method of, and system for, real estate index generation

Assignee: ARES CAPITAL MAN PTY LTDPriority: Feb 26, 2007Filed: Jan 17, 2013Published: Oct 3, 2013
Est. expiryFeb 26, 2027(~0.6 yrs left)· nominal 20-yr term from priority
G06Q 50/16G06Q 40/06G06Q 40/04
42
PatentIndex Score
0
Cited by
0
References
0
Claims

Abstract

A method and system for generating a real estate property index uses real estate data including price data, property data and time of sale data that are entered into a computing apparatus. The time of sale data is manipulated to provide consecutive triple times giving two consecutive time periods (e.g., March, April, May 2007 and April, May, June 2007). A transform function, preferably a long function, is generated with two time dummy variables, and the coefficients of the two time dummy variables are extracted and added to generate a transformed growth rate. The reverse transform function, preferably an anti-log function, is generated to provide the desired untransformed growth rate.

Claims

exact text as granted — not AI-modified
1 . A computer-implemented method of generating a digitally encoded electric signal which represents a real estate property index, the method comprising:
 inputting into a data store of a computing apparatus real estate data comprising property data, price data and time of sale data representing historical real estate sales transactions in a predetermined real estate market,   using said computer apparatus to manipulate said real estate data to group same into consecutive triple times based on said time of sale data,   using said computer apparatus to generate a transform function using said manipulated data with two time dummy variables corresponding to two consecutive time periods respectively bounded by the triple consecutive times,   using said computer apparatus to extract the coefficients of the two time dummy variables of said transform function for said two consecutive time periods,   adding said two extracted coefficients in said computer apparatus to generate a transformed growth rate from the first to the last of said triple times, and   generating said digitally encoded electric signal which represents said index from said transformed growth rate by calculating the reverse transform function thereof.   
     
     
         2 . A computer-implemented method of generating a real estate property index, the method comprising:
 inputting into a data store of a computing apparatus real estate data comprising property data, price data and time of sale data representing historical real estate sales transactions in a predetermined real estate market,   using said computer apparatus to manipulate said real estate data to group same into consecutive triple times based on said time of sale data,   using said computer apparatus to generate a transform function using said manipulated data with two time dummy variables corresponding to two consecutive time periods respectively bounded by the triple consecutive times,   using said computer apparatus to extract the coefficients of the two time dummy variables of said transform function for said two consecutive time periods,   adding said two extracted coefficients in said computer apparatus to generate a transformed growth rate from the first to the last of said triple times, and   generating said index from said transformed growth rate by calculating the reverse transform function thereof.   
     
     
         3 . The method of  claim 2 , wherein said transform function comprises a logarithmic function and said reverse transform function comprises an anti-log function. 
     
     
         4 . The method of  claim 2 , wherein said logarithmic function has the form 
       
         
           
             
               
                 log 
                  
                 
                     
                 
                  
                 
                   
                     P 
                     i 
                   
                    
                   
                     ( 
                     t 
                     ) 
                   
                 
               
               = 
               
                 
                   α 
                    
                   
                     ( 
                     t 
                     ) 
                   
                 
                 + 
                 
                   
                     ∑ 
                     
                       j 
                       = 
                       1 
                     
                     N 
                   
                    
                   
                       
                   
                    
                   
                     
                       β 
                       j 
                     
                      
                     
                       
                         f 
                         j 
                       
                        
                       
                         ( 
                         
                           X 
                           
                             i 
                             , 
                             j 
                           
                         
                         ) 
                       
                     
                   
                 
                 + 
                 
                   
                     ∑ 
                     
                       t 
                       = 
                       1 
                     
                     T 
                   
                    
                   
                       
                   
                    
                   
                     
                       λ 
                        
                       
                         ( 
                         t 
                         ) 
                       
                     
                      
                     
                       D 
                        
                       
                         ( 
                         t 
                         ) 
                       
                     
                   
                 
                 + 
                 
                   
                     ɛ 
                     i 
                   
                    
                   
                     ( 
                     t 
                     ) 
                   
                 
               
             
           
         
         wherein 
         P i (t) is the selling price of property i at time t, 
         α(t) is the intercept term, 
         X is a vector of the N hedonic attributes included in the model, 
         β j  is the regression coefficient reflecting the implicit price of j th  attribute, 
         λ(t) estimates the cumulative growth rate to time t, 
         D(t) is a set of dummy variables equal to 1 if the property sold in time-period t and zero otherwise, and 
         ε i (t) is the random variation in price of property i at time t unaccounted for by the other terms. 
       
     
     
         5 . The method of  claim 4 , further comprising:
 transforming attribute values Xj of said logarithmic formation by continuous piecewise linear functions f j  prior to determining to coefficients β j  via multi linear regression.   
     
     
         6 . The method of  claim 3 , wherein said logarithmic function is: 
       
         
           
             
               
                 log 
                  
                 
                     
                 
                  
                 
                   P 
                   i 
                 
               
               = 
               
                 
                   
                     c 
                     0 
                   
                    
                   
                     ( 
                     
                       T 
                       k 
                     
                     ) 
                   
                 
                 + 
                 
                   
                     ∑ 
                     
                       j 
                       = 
                       1 
                     
                     m 
                   
                    
                   
                       
                   
                    
                   
                     
                       
                         s 
                         j 
                       
                        
                       
                         ( 
                         
                           T 
                           k 
                         
                         ) 
                       
                     
                      
                     
                       S 
                       j 
                     
                   
                 
                 + 
                 
                   
                     ∑ 
                     
                       j 
                       = 
                       1 
                     
                     n 
                   
                    
                   
                       
                   
                    
                   
                     
                       
                         c 
                         j 
                       
                        
                       
                         ( 
                         
                           T 
                           k 
                         
                         ) 
                       
                     
                      
                     
                       
                         f 
                         j 
                       
                        
                       
                         ( 
                         
                           x 
                           j 
                         
                         ) 
                       
                     
                   
                 
                 + 
                 
                   
                     
                       λ 
                       1 
                     
                      
                     
                       ( 
                       
                         T 
                         k 
                       
                       ) 
                     
                   
                    
                   
                     τ 
                     1 
                   
                 
                 + 
                 
                   
                     
                       λ 
                       2 
                     
                      
                     
                       ( 
                       
                         T 
                         k 
                       
                       ) 
                     
                   
                    
                   
                     τ 
                     2 
                   
                 
                 + 
                 
                   ɛ 
                   k 
                 
               
             
           
         
         where: 
         the ƒ j  are transformations of the hedonic variables, 
         the c j  are time varying numerical coefficients, 
         the S j  are dummy variables with S j =1 if property i is in suburb j., 
         the s j  are time varying numerical coefficients of the suburb dummy variables, 
         τ 1  is a dummy variable with τ 1 =1 if the sale occurred in period T k−1  and τ 1 =0 otherwise, 
         τ 2  is a dummy variable with τ 2 =1 if the sale occurred in period T k  and τ 2 =0 otherwise, and 
         ε k  is the (zero mean) residual error term. 
       
     
     
         7 . The method of  claim 3 , wherein the logarithm of sale prices is linear with respect to the logarithm of land sizes. 
     
     
         8 . The method of  claim 3 , further comprising:
 for each set of triple times, regressing said logarithmic function against the logarithmic of land prices to obtain an index growth rate.   
     
     
         9 . The method of  claim 3 , further comprising:
 using a mean square error estimation method to adjust the convexity of said logarithmic function.   
     
     
         10 . The method as claimed in  claim 2  wherein said index comprises a capital gains index. 
     
     
         11 . The method of  claim 2 , further comprising:
 adding an imputed or actual rental income for each of two consecutive time periods to form an accumulation index.   
     
     
         12 . The method of  claim 11 , wherein said rental income is regressed. 
     
     
         13 . The method of  claim 2 , further comprising periodically rebasing said index to accurately represent changes in value in said real estate market over extended periods of time, and/or to accurately represent absolute market prices. 
     
     
         14 . A computer-implemented system for generating a digitally encoded electric signal which represents a real property index, the system comprising:
 a data storage device into which is input real estate data comprising property data, price data and time of sale data representing historical real estate transactions in a predetermined real estate market;   a data manipulator connected to said data storage device to manipulate said real estate data into groups of consecutive triples times based on said time of sale data;   a transform generator connected to said data manipulator to generate a transform function using said manipulated data with two time dummy variables corresponding to two consecutive time periods respectively bounded by a triple consecutive times;   a coefficient extractor connected with said transform generator to extract the coefficients of the two time dummy variables of said transform function for said two consecutive time periods;   an adding circuit connected to said coefficient extractor to add said two extracted coefficients to generate a transformed growth rate from the first to the last of said triple times; and   a reverse transfer function generator connected to said adding circuit to generate said digitally encoded electric signal which represents said logarithmic growth rate by calculating the reverse transform of said transformed growth rate.   
     
     
         15 . The system of  claim 14 , wherein said transform function comprises a logarithmic function and said reverse transform function comprises an anti-log function.

Join the waitlist — get patent alerts

Track US2013262284A1 — get alerts on status changes and closely related new filings.

We store only your email — no account needed. See our privacy policy.