USER MANUAL
Contents
1. ina 19 The following interface will appear TE Market Conditions Analysis a F Choose the Chart Display Chart Date of property valuation Value Trend sic aa arai Market Activity Trend Onday BE pri Best Fit Degree E Perform Market Adjustment Choose the best fit Click here to adjust all of the sales used in the regression analysis for time and then re run the regression analysis based on the time adjusted sales price Print a report or copy directly into your appraisal report 20 Market Conditions Analysis Comments Put comments here that you want in the report Enter comments for the report here Manually Adjusted Values Sale Date Sale Price DF Dit Adj Price 01 09 09 i 234 500 00 43 1 101 108 133 392 00 Fnter the date and sales price of the sales comparables here and the time adjustments will be returned based on the trend line for use in the direct sales comparison approach Note For illustrative purposes the example used here has an extreme fall in the value trend hopefully your real trend line will not fall so steeply2. REGRESSION for Real Estate Professionals with Market Conditions Module USER MANUAL Automated Valuation Technologies Inc Regression For Real Estate ProfessionalsO with Market Conditions Module This Regression software program and this user s manual have been created by Automated Valuation Technologies Inc AVT The purpose of AVT is to fill the voids in appraisal practice that result from the rapidly changing appraisal environment Appraisers often find themselves engaged in new activities which require the use of technology that has not yet been created This is both unfortunate and unacceptable It is unfortunate because appraisers are not fully effective in carrying out their duties It is unacceptable because it compromises the vital role appraisers perform in the safekeeping of their country s greatest wealth real property It is AVT s mission to provide the technologies real estate appraisers require to fulfill their duties AVT operates under the belief that there is no substitute for the Neighborhood Appraiser Their knowledge of the local market is unique and cannot be duplicated by remote computer analysis These local appraisers are hardworking and dependable Without question these gritty individuals will carry out their duties as long as they have the knowledge and tools to do so This manual and the accompanying software program are copyrighted 2008 Automated Valuation Technologies Inc
3. 215 Ellis Avenue Maryville TN 37804 TABLE OF CONTENTS Contents O AREE E EE A A E TENSS 4 SY STEIVWREQUIREIVIEINTS o e O OO 4 LOADING THE PROGRAM AND GETTING STARTED 0 00 cccececcceccccccccccccecececececererscererevererererseseceneasens 4 COMPONENTES casi a a no ea e anio debo ea Aaa 6 TORES DES io e no de e Se E E 6 IMPORTEEATUR Ecco iconos cotas dd Oe sis 7 DATA SERUBDE renon e Ph EN ee en Ure Cee CC ee Tee 8 DERINE THE VARIABLES e ae aes 9 PROPERTY VALUATION PARAMETER Som adi s 10 REGRESSION SCREEN a e a dd e da a 11 TREND ANAL SS cana 12 CONFIDENCE RATING CHECCS Te senos da o a tos al alo e Lu aed 13 PRI SESA VE oa to cis Ter ort 14 STEPS TO PERFORM A REGRESSION ANAL Sussie ed a cod o sees 15 MARKET CONDITIONS MODULE a sor Doc SOLES 16 PURPOSE The purpose of the Regression application is to provide all of the power of a regression analysis in a format that is simple and easy for real estate professionals to use This product is suitable for variety of uses by most any real estate professional A partial list of users includes appraisers sales agents review appraisers mortgage lenders investors etc A partial list of uses includes extracting adjustments and predicting sales price rent rates capitalization rates etc The purpose of this user manual is to provide instructions on using the Regression application It is not intended to teach the theory of Regression Analysis or how to best perform such an
4. 0 0 000N 0 931 The P factor is a 5 a 5 z a Baths 1121090 Ju 0 034 Yoo z ra iesi 6 oe 937 measure of the E 7 7 7 i likely hood that the Selected Exempt No Sales Price GLA BR DSS Baths Age Predicted V lDif AbsDiff O 1 125235 1663 3 365 1 17 13947965 1424465 1137 output was A 163123 1578 3 380 2 i 14477048 1835252 1125 randomly AE 132041 1666 a 360 1 17 14767729 1473629 1108 A i 139853 1614 4 340 3 16 16679640 2694340 19 27 determined Ol s 203019 2306 1 32200 3 23 19171441 1130459 557 rls 133484 1585 2 300 1 16 12629048 719152 539 DN gt 147944 694 3280 347 160600591 1573891 1064 The SubDev is a gie 149661 1615 3 260 2 16 14785426 180674 121 BAE 234071 2351 4240 224 20731842 2675258 1143 measure of how lus C 10 177000 1074 q1 7AN q AA similar each subject variable is to those in the model Check to exempt a record from The Weight is the being automatically removed by amount that the variable the remove outlier button was used in calculating the subject s value 11 TREND ANALYSIS _ Regression for Real Estate Professic To begin the trend File Valuation analysis Remove Outhyer 19 27 e A a Valuation Settings oe Set Confidence Rating 09 37 i 06 07 a a 02 77 E The user should explore 00 53 o 9 a why any straight line 03 832 o pal varies more than about D 2 5 in accuracy 07 13 C amp o e qe y 10 43 JO The polynomial
5. analysis strongly recommend that the user take the regression seminar that is associated with the Regression applicationO E mail dbraun braunappraisal com for information on where to find information on this class The book A Guide to Appraisal Valuation Modeling by Linne Kane and Dell is a recommended source for information on the various methodologies associated with regression analysis SYSTEM REQUIREMENTS Regression has the following system requirements e Windows XP Service Pack 1 or newer or Windows Vista e Microsoft NET Framework version 2 0 or 3 0 e 10MB Hard Drive space available For importing Excel 2007 documents xIsx xlsm Microsoft Office 2007 or Excel 2007 is required to be installed However Microsoft Excel 2007 is not required for importing Excel 2003 or earlier documents xls This program will not run across a network it must be loaded on your CAY drive LOADING THE PROGRAM AND GETTING STARTED You re CD contains the following important things 1 The User Manual 2 Regression Loader 3 The Case Studies a An Excel file with the sample data 4 Athree part tutorial video 5 Microsoft NET Framework version 3 0 Loading the Regression Plus program This program requires that either NET Framework 2 0 or 3 0 is installed on your computer To verify that you have one of these versions loaded go to Control Panel them Add remove programs If you do not see Microsoft NET F
6. categories a Descriptive b Dependent Variable c Independent Variable 7 Load the data into the regression analysis and check the data for a Blanks b Text and c Outliers 8 Enter the subject information 9 Perform the regression analysis by adding or subtracting variables and checking the Trend Analysis for each individual variable used 10 Complete the confidence rating check list 11 Report a Print out the report b Copy the report into MS Word or your appraisal report c Convert to an Adobe pdf file 15 MARKET CONDITIONS MODULE The Regression program is a multi linear system This system is easy to understand and works reasonably well for most real estate applications However there are times when a property characteristic simply does not conform to a straight line analysis tool The market condition Time adjustment MCTA that has resulted in many areas of the Country since the Real Estate Crash of 2007 is a good example of such a property characteristic The new Market Conditions Analysis module is designed to provide additional tools based on multi linear regression analysis to aid the valuation professional in meeting the challenges in market condition changes other than a constant straight line scenario Y axis Value Trend 5204 23 5184 23 164 23 144 23 124 23 5104 23 584 23 The above chart plots the sales price per square foot over time Notice that the blue line tends to fit
7. fF appraiser Adjusted R squared 60 69 70 79 Mostly yellow no Reds Mostly Green no Reds All Greens 13 PRINT amp SAVE Regression for Real Estate Professiona New Valuation Open Valuation Save Valuation Save Valuation As Copy Report Print Report Print Preview Page Setup Exit 110000 130000 150000 O tn 3 190000 Selected Exempt No Sales Price GLA BR 14 STEPS TO PERFORM A REGRESSION ANALYSIS Be sure to watch the three part video and work through the Case Studies which are found on the Regression CD 1 Collect the data 2 Organize the data on an Excel Spreadsheet 3 Identify and make a note of the columns that will utilize the Regression s scrubber system a Days since sale DSS must be used instead of the date of sale as a date is an illegal format b If your MLS or other data source has a field for full and half baths the scrubber can combine these fields for you c The year built is best converted to age as this will result in a smaller intercept d The scrubber will convert a column of text entries into numeric columns for each unique value e The scrubber will add two columns together and create a new column for the sum 4 Transfer the data to the Regression by either a Directly from the Excel workbook via a browser or b Copy the data to the MS Clipboard and paste into the Regression 5 Setup the scrubber 6 Identify the columns to be used by
8. 0 2009 e Divide sales date into periods for Market Conditions Analysis MCA Column Indicating the Sale Date Date i Time interval span days E we 1 Combine the total number of full and half bathrooms Note the Dummy field set up in the scrubber Use both the Calculate number of days since sale and the Dummy field set up You can decide which one to use later 17 lables from the list on the left and move ight that those fields will play Descnptive Columns The identity of the property such as the address Dependant Vanable Usually the property sale price Independant Variables qeria the The fields on which to do the regression analysis ields as an independent variable MCA Fields 18 Value 154 114 98 Observations E el ji ns MMF Rating 90 5 Adjusted R2 0 917 CoD Rating 5 4 Remove Outhrer Valuation Settings Set Valuation Confidence Rating Selected Variable Value Weight Sul a Note the Dummy l l Intercept 16 820 71 5 fields will be set up ELA 08 95 59 automatically for you BR 447 98 g The data spanned six Baths 1011343 Fe sixty day periods Age 3 290 04 19 Days5incesale 118 34 0 MCABD_1 10 858 72 0 MCABO 2 42 491 13 0 MCA6D_3 15 765 77 0 YP MCA6D 4 9 371 47 0 MCABO_5 520 774 38 0 MCA6D_6 34 073 04 0 Regression for Click on Valuation 13 13 then Market Condition Analysis
9. IMPORT FEATURE The data may be loaded directly from an open or closed MS Excel File or from the MS Clipboard 41 Create a Regression Document JON Step 1 Load Data IE mis The first row of data contains J From Excel File From Clipboard cian Data Loaded Sales Price GLA 126 985 1 663 136 208 1 578 159 986 1666 161 902 1614 173 793 2306 147 376 1585 180 976 1 684 163 718 1 615 205 292 235 4177 052 1 923 138 557 1 935 124 450 1494 147 023 1719 150 708 1 493 e lez 1 2 3 4 5 50 Ca ij on dhe Ba PS DATA SCRUBBER The data scrubber helps you to prepare data for the regression analysis For example the days since sales DSS are used in place of the actual sales dates because the regression analysis requires all of the data to be numbers G Create a Regression Document COS Step 2 Scrub Data O Calculate the number of days since the sale date O Combine the total number of full and half bathrooms Calculate the age of the property at time of sale O Split the following text column to numeric columns for each unique value O Add the following two columns into a third G Create a Regression Document JON Step 3 Scrub Data Some More Remove Records Rows that have no data in the following checked fields Columns C No C Sales Price F GLA O ER F pss C Baths C Age Unchecked fields will default to a value of zero wh
10. ay October 28 2008 Value Comparable List Other Factors here added or subtracted from the regression analysis value This includes anything that effects value but was not considered in the data sample Some examples might be view lot size closing costs etc 10 REGRESSION SCREEN R squared is the amount of the market s behavior that is described by the regression model This is the value that The adjusted R squared is a more This Chart shows the the conservative approach to R squared percentage that the model regression missed actual sales price by analysis MMP is the Market Model s Predictive predicts ability based on the sample CoD is on the latest version It is the Coefficient of Disbursement Use this button to remove outliers automatically starting with the record where the model has the highest predictive error The Valuation 4 Reglession for Real Estate Professionals Untitled Valuation p JOR Setting button File Valuation sil allows you to enter 19 27 Value 90 000 01 the subject 15 97 Observations 50 MMP Rating 3 R2 0 748 12 67 Adjusted R 0 719 87 3 information 03 37 Valuation Settings 06 07 02 77 Set Valuation Confidence Rating he Value is the model s output for 00 53 Selected Variable Value Weight SubDev P 03 83 Intercept 11 959 98 6 the characteristic 07 13 GLA 51736 67 DI 0 366 10 43 BR 7 956 34 WT 0 404 0 000 o DSS 1 85
11. be added back in by a simple click 7 Numerous readings to help complete the analysis a The number of records considered in the sample b A measure of the Market Model s predictive power MMP c The R squared and the adjusted R squared d The weight assigned to each property component by the model e The P factor for each property characteristic f Ameasure of each of the subject property s components fit to the components in the data sample SubDev g Ameans of identifying sudden changes in the value relationship of each property component by Error Trend Analysis 8 Perform Step wise or reverse step wise methods of analysis at the click of a button 9 Select or deselect any record on the fly 10 A comprehensive checklist to help the user assign an Over all confidence rating to the prediction 11 Acomment box for any narrative that the user wishes to include in the report 12 The Valuation Settings a Where the subject property s characteristics independent variables are entered b Add or deduct for any property characteristics not considered in the regression analysis c Set the rounding of the final value 13 Print the Report THRESHHOLDS The P Values and Subject Deviation values are coded as follows P Value Green lt 0 15 Red gt 0 3 Yellow otherwise between 0 15 and 0 3 Subject Deviation Green lt 1 0 Yellow gt 1 0 but within the observation range Red Outside the observation range
12. en a record has either no information or non numeric information in that field DEFINE THE VARIABLES Identify and choose the data to be used iJ Create a Regression Document Step 4 Define Variables Select the fields columns from the list on the left and move them into the roles on the right that those fields will play Descnptive Columns The identity ofthe property 2fich as the address Dependant Variable Usually the property salp erice Sales Price Independant Variables The fields on which to do the regression angles Descriptive Columns contain information like address or listing number This information is not used in the analysis The Dependent Variable is what you are trying to find such as sales price rent per square foot etc The Independent Variables are the things that are analyzed to predict the dependent variable PROPERTY VALUATION PARAMETERS Set the Rounding here Set the Decimals here Property Valtuation Parameters Output Value Display in currency format Number of whole places to round 0 Number of decimal places to display 2 Property Charactenstics Other Factors Characteristic Value Other Factor capas A PS DSS 186 Baths 2 Age 18 Add Factors Enter the Independent Variables for the subject property here Set the effective date of the apprajsal here Sample Output Value Display 123 456 79 Date of Appraisal Tuesd
13. feature Diiia a may help explore the i a Situation l ie Selected Exempt No Sales Price GLA BR DSS Ba le A ere T663 3 E 2 163123 1578 3 380 Tal 1 a PD Ar a a ia g i m Lx X This chart plots the selected Independant Variable against the price diference between the sample properties and their predicted model value The resulting best fit line may show a trend in the accuracy of the model in relation to the variable chosen GLA BR DSS Baths O Age a F iD a a x Ped PJ Gu Lil Lo a mua oo Plot the price diff as Best Fit Degree a Absolute signed 1 El lose 12 CONFIDENCE RATING CHECK LIST w Confidence Rating Evaluation Jee Acceptable 1 Number of Observations 2 Quality amp Accuracy of Data Sample 3 Market Model s Prediction MMP Accuracy 4 Subject Property s Fit to the Data Sample 5 Reasonability of Model s Outputs for Characteristics 6 Weight Applied by Model 7 Adjusted R Squared 8 P Factors The Over all Confidence Rating Additional Comments You may add comments to be presented in your report here Acceptable 20 29 49 Data Sample Quality Determined by appraiser 80 84 85 90 Similarity of subject to Yellows reds are OK if Greens amp Yellows reds All Green the sales SubDev they have low weight are OK if they have low weight econo ease O appraiser e lec
14. ramework v 2 0 or 3 0 listed then load from the Regression CD It is OK to have other versions of NET Framework loaded in addition to the version 2 0 or 3 0 E a Insert the CD into your computer Open the file Regression msi that is on the CD Once you are in the Setup Wizard click on the Next button When the License Agreement becomes visible read it carefully If you agree to the terms of this agreement then choose I Agree and click on the Next button Select the installation folder If possible use the default folder which is shown by default Do not load on a network drive although multiple users may save their documents to a folder ona network drive The Disk Cost button allows you to compare the size of the program to the installation location chosen Most users will not need to use this feature For most users select Everyone When asked to confirm installation click the Next button There will be a new shortcut on your desktop Click it to open the Regression Plus program COMPONENTS 1 Import Feature a Directly from an open or unopened Excel workbook b Directly from the MS Clipboard 2 Data Scrubber 3 Loader loads the scrubbed data into the regress analysis 4 Regression Engine 5 Achart depicting the absolute error of each record in the data sample 6 Aremove outlier feature a Records can be marked excluding them from being removed b Any removed record can easily
15. the data better than the straight red line In a situation like this an analysis based on a straight line will not return accurate results 16 The new Market Condition Analysis Module is designed to help you perform the following e Extract the market s value trend line based on the adjusted sales price using dummy fields e t will create both a value trend line and a volume trend line e Utilize the trend line to o Determine if a straight line analysis is appropriate for the market condition trend o Forman opinion concerning the direction of the value trend o Make the appropriate market condition adjustments to the comparable sales used in the direct comparison approach o Adjust all of the sales in the regression analysis for market conditions and then rerun the regression based on the time adjusted sales prices Utilizing a trend of the adjusted sales price per property is much more accurate that one based on the unadjusted sales price or based on the adjusted sales price per square foot These new features are enhanced with reporting options The emphasis of this module is to enable the user to perform these advanced techniques in a matter of just a few minutes This accomplished by programming these tools into the user interface T Create a Regression Document step 2 Scrub Data Calculate the number of days since the sale date Column Indicating the Sale Date Date we Date of Appraisal __ Monday Apl 2
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