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System, method and computer program for forecasting residual values of a durable good over time

  • US 9,607,310 B2
  • Filed: 08/14/2013
  • Issued: 03/28/2017
  • Est. Priority Date: 08/15/2012
  • Status: Active Grant
First Claim
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1. A system for forecasting future values of an item, the system comprising:

  • a server computer coupled to a network; and

    a local data storage device coupled to the server computer;

    wherein the server computer is configured to;

    receive or collect different types of data over the network from data sources external to the system, the different types of data including modifications, locality, depreciation, microeconomic data, macroeconomic data, and competitive sets;

    wherein the server computer has one or more crawlers configured to query at least one or more of the data sources external to the system;

    wherein the modifications reflect any changes to an item that affect a value thereof at any time point;

    wherein the locality represents valuation differences in an industry that vary geographically;

    wherein the depreciation represents a natural change in value that occurs as the item is used over time;

    wherein the microeconomic data comprises information that is specific to an industry of the item;

    wherein the macroeconomic data comprises information that is nonspecific to the item and the industry of the item; and

    wherein the competitive set relates to a set of items that compete with the item in the industry of the item;

    store the different types of data received or collected by the server computer in the local data storage device;

    identify portions of the different types of data stored in the local data storage device for generation of a residual value forecast for an item of interest;

    perform a scrubbing process to scrub the identified portions of the different types of data to improve data quality of the data by and provide an improved basis for the forecast, the scrubbing process comprising identifying and removing erroneous data from the identified portions of the different types of data and removing outlying data points from the identified portions of the different types of data, the scrubbing process generating a modified data set;

    store the modified data set in the local data storage device, the modified data set comprising past sales of a plurality of items in the industry;

    determine an initial value for the item of interest based on the past sales of the item of interest or items that are similar to the item of interest;

    determine an item value adjusted from the initial value to account for modifications to the item of interest and locality of the item of interest;

    determine one or more future values for the item of interest utilizing the item value of the item of interest and based at least in part on a rate of depreciation of the item of interest over time, microeconomic data specific to the industry of the item of interest, and macroeconomic data non-specific to the item of interest and the industry of the item of interest, the macroeconomic data including economic information relating to the overall economy including consumer wage information and prices of goods unrelated to the plurality of items in the industry, the one or more future values forming a residual value curve and representing the residual value forecast for the item of interest;

    store the one or more future values in the local data storage device;

    provide the one or more future values to a client device over the network for display on the client device via a user interface;

    receive editorial input over the network via the user interface displayed on the client device;

    modify the one or more future values stored in the local data storage device based on the editorial input to account for factors that affect the one or more future values that have since changed or were not accounted for in the determining of the one or more future values;

    automatically modify the one or more future values at regular intervals without user intervention, based at least on competitive set information relating to a set of items that compete with the item of interest in the industry of the item of interest;

    store the one or more modified future values in the local data storage device; and

    responsive to a request from a client device to view the residual value forecast for the item of interest, provide the one or more modified future values to the client device over the network.

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