Fannie Mae Mar 2008 - Oct 2012
Financial Engineer I, Ii, Iii, Iv
Fannie Mae Mar 2008 - Oct 2012
Economist Iii
Jpmorgan Chase & Co. Mar 2006 - Mar 2008
Statistician I
Education:
University of Washington 2005 - 2005
Bachelors, Bachelor of Science, Economics
Skills:
Credit Risk Sas Quantitative Analytics Valuation Analysis Econometrics Financial Modeling Sql Economics Financial Analysis Credit Scoring Residential Mortgages Appraisals Sas Programming Loan Portfolio Analysis Statistical Modeling Basics of Unix Financial Risk Analytics Quantitative Finance Time Series Analysis Avm Valuation Modeling Loans Underwriting Statistics Economic Modeling Market Risk Mortgage Lending Unix
Us Patents
Automated Valuation Model With Comparative Value Histories
David A. Talbird - Bronx NY, US Megan C. Berry - Rockville MD, US Felix G. Meale - North Bethesda MD, US Eric Rosenblatt - Derwood MD, US Jesse Staal - Arlington VA, US
Assignee:
Fannie Mae - Washington DC
International Classification:
G06Q 50/16
US Classification:
705306
Abstract:
An automated valuation model and corresponding analysis tool that graphically displays value history information in association with a subject property is disclosed. In one example, the tool generates a graph plotting the valuation history of a subject property over an adjustable time range in relation to a general price index for a pertinent geographical area. When looking at an appraisal for a property, the graph also supports selective plotting of appraiser-selected comparable properties' valuation histories against that of the subject property. The valuation history for comparable properties can be scaled on a pro-rata basis according to the percentage of the adjustments made within the appraisal. In addition, the graph selectively incorporates model-generated comparables and their valuation histories.
Automated Valuation Model Using Ordinal Variables Such As Condition And Quality Variables
John Treadwell - Washington DC, US Lisa Dorsey - Arlington VA, US Patria Kunde - McLean VA, US Eric Rosenblatt - Derwood MD, US Jesse Staal - Arlington VA, US
Assignee:
Fannie Mae - Washington DC
International Classification:
G06Q 50/16
US Classification:
705306
Abstract:
An automated valuation model that uses condition and quality variables. In response to user queries, the model ranks and displays comparables for a subject property. The comparables are selected based on their similarity to the subject. Data on quality and condition of properties is incorporated into the model and corresponding comparable assessments. For example, the quality and condition inputs may be used in a hedonic adjustment factor model, comparable selection exclusion rules, economic distance calculations, and adjustments for differences between the subject and comparables at comparable selection stage. The comparables may be displayed in ranked order based on the calculated similarities between the properties, with indications of the quality and condition categories, to provide an overall assessment of the comparables as well as displayable indications of the underlying quality and condition categories and related information. The model may also use other ordinal variables and may perform any type of valuation.
Selecting Properties Using Location Constraints Based On Travel Time Contours
- Washington DC, US Steven Pierce - Annandale VA, US Eric Rosenblatt - Derwood MD, US John Treadwell - Washington DC, US Jesse Staal - Washington DC, US
International Classification:
G06F 17/30 G06Q 50/16
Abstract:
A database of property data is searched based on a location constraint that is determined based on travel time contours constructed for multiple locations of interest. The locations of interest and travel parameters associated therewith are selected by a user. The travel parameters include a maximum travel time for each location. For each location, the travel time contour is constructed based on the travel parameters for the location such that points within the travel time contour have a travel time to the location that is less than or equal to the maximum travel time. The travel time contours are intersected, and the location constraint is based on the intersection.
- Washington DC, US John Treadwell - Washington DC, US Eric Rosenblatt - Derwood MD, US Jesse D. Staal - Washington DC, US Fotis Gavriil - Vienna VA, US
International Classification:
G06Q 30/02 G06F 17/30 G06Q 50/16
Abstract:
Continuous property-level location effects may be determined by generating property-level location effect functions that map location coordinates to property-level location effect values. Each property-level location effect function corresponds to a sub-region of a larger region, the larger region being a region to which a hedonic equation of an automated valuation model corresponds. Each of the property-level location effect functions may be generated by fitting a set of data points that correspond to the sub-region for which the function is being generated. The set of data point to which a given function is fitted are based on the differences between model-estimated values and actual values (e.g., sales prices) for each of the properties located in the corresponding sub-region and in at least one adjoining sub-region. The property-level location effects functions are continuous and vary within their respective sub-region according to property-level changes in location effect.
Assessing Quality Of A Location With Respect To Its Proximity To Amenities
- Washington DC, US Steven Y. Pierce - Annandale VA, US Eric Rosenblatt - Derwood MD, US John Treadwell - Washington DC, US Jesse D. Staal - Washington DC, US
International Classification:
G06Q 30/02 G06Q 50/16
Abstract:
A method and system for computing an amenity score for any arbitrary point in a given geographic area. The amenity score may take into account a variety of amenity types and an optional list of user-prioritized amenity types, to compute a score that measures the overall amenity availability for that location. The amenity score may be determined by identifying amenities, assigning a unit function to each identified amenity, summing unit functions to obtain an integrated function for each amenity type, and combining the integrated functions into an amenity score function.
Evaluating Condominium Appraisals Using Project As Location Effect
- Washington DC, US Eric Rosenblatt - Derwood MD, US Jesse Staal - Arlington VA, US Lin Feng - Rockville MD, US Weifeng Wu - Arlington VA, US
International Classification:
G06Q 30/02 G06Q 50/16
Abstract:
Modeling appropriate comparable properties for the assessment of appraisals entails accessing a property dataset, wherein subsets of properties represented in the property data are determined to be members of respective condominium projects. Condominium project identification information is scrubbed, standardized and updated using various techniques. An automated valuation model is applied to the property data, preferably implementing the condominium project variable as a location fixed effect variable. Appraisal reports where the subject property is a condominium are then analyzed using the results of the automated valuation model, including but not limited to ranking and displaying the appraiser-chosen comparables among the model-chosen comparables.
Dynamic Display Of Representative Property Information With Interactive Access To Source Data
- Washington DC, US Eric Rosenblatt - Rockville MD, US Jesse Staal - Arlington VA, US David A. Talbird - Bronx NY, US Angela Tseng - Germantown MD, US
Assignee:
FANNIE MAE - Washington DC
International Classification:
G06F 17/30 G06Q 40/00 G06Q 50/16
Abstract:
A system and method may aggregate into a data structure property information from multiple databases, e.g., from all records included in those databases, and upon selection of any subject property or a characteristic thereof curates the often imperfect and discrepant property information to create suggested values. Similarly, the system and method may perform an on-the-fly evaluation of any characteristic of a selected record, when the property information for that characteristic includes an unlikely value, by triggering from the data structure a dynamic extraction of property information corresponding to a subject property of the selected record, where the dynamic extraction further generates and compares a suggested value to the unlikely value.
Performing Automated Appraisals With Automatic Detection And Remediation Of Situations Involving Faulty Characteristics
- Washington DC, US Felix G. Meale - North Bethesda MD, US Eric Rosenblatt - Derwood MD, US Jesse Staal - Arlington VA, US Angela Tseng - Germantown MD, US
Assignee:
Fannie Mae - Washington DC
International Classification:
G06Q 30/02
Abstract:
Performing automated appraisals with automatic detection and remediation of situations involving faulty characteristics is disclosed. Property information characteristics are extracted from properties listed on electronic appraisals. For a subject property, faulty characteristics include the absence of characteristics, or errors in characteristics. Such faulty characteristics are those that would cause an automated appraisal of the given property to be invalid or unsuitable. In response to the detection of faulty characteristics, interfaces may solicit input addressing the faulty characteristic and upon remediation indicate a clean and complete characteristic set. Thereafter, automated appraisal of the subject property based on the clean characteristic set is initiated to provide an automated valuation of the subject property.
Youtube
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thepensblog.com
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27 Nov, 2010
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