Computerized art investment estimation system

#Each year, works of art are sold at a wide variety of venues. Works of art that are available for sale may be hundreds of years old or relatively new works; they may be produced by well-known artists, relatively unknown artists, or artists who are newly discovered. For works of art that have been produced by artists with established reputations or who are currently popular, art auctions represent a certain percentage of works of art that are available for sale in any given year. Art auction houses may determine the price of a work of art to be auctioned based on a number of variables, including market trends, comparative sales, estimated buyer interest, and so forth. Although buyers of art may purchase a particular work of art out of personal interest, investment potential may also be of significant interest to art buyers.

#A computerized art investment estimation system is provided. The system may include a processor and associated memory. The processor may be configured to execute one or more programs stored in the memory to store, in the memory, a database that may be continually updated to include a first sale price and associated first sale date and a second sale price and associated second sale date of a plurality of repeat sale pairs of a plurality of works of art associated with an artist. The processor may be configured to determine one or more investment value variables derived at least from the first sale price and associated first sale date and the second sale price and associated second sale date for the plurality of repeat sale pairs of the plurality of works of art. The processor may be configured to receive, at a graphical user interface (GUI), input from a user designating weights for the one or more investment value variables. The processor may be configured to determine, from the designated weights and the one or more investment value variables, an artist investment potential value for the artist and, at the GUI, display to the user the artist investment potential value.

#This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.

#A more complete appreciation of the invention and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings.

#FIG. 1 shows a computerized art investment estimation system according to an example implementation of the present disclosure.

#FIG. 2 shows a flowchart of an algorithm for calculating market adjusted risk per unit of return ratio implemented by an estimator program of the system of FIG. 1.

#Determining the value of a work of art has been known to include an element of precariousness. Estimates of the value of a given work of art may be produced by professional evaluators and/or auction houses and may attempt to account for liquidity, historical sales data, current buyer interest, and other relevant factors. However, historically within the art market there has been a lack of reliable measures of the industry that may provide solid indicators of investment values for works of art by a particular artist. As such, a buyer interested in art as an investment may find little transparent information on how to choose a work of art for purchase.

#Systems and methods for an art investment estimation are described herein. FIG. 1 shows a computerized art investment estimation system 12 according to an example implementation of the present disclosure. The system 12 may be implemented using one or more computing devices 14, each of which may include a processor 16 and associated memory. The associated memory may include volatile memory 18 and non-volatile memory 20. The processor may be a CPU, GPU, FPGA, ASIC, or other type of processor or integrated circuit. The processor 16 may be configured to execute one or more programs, such as estimator program 17, stored in the memory, specifically in the non-volatile memory 20. System 12 is illustrated as a client-server system, in which computing device 14 is configured as a server, which is capable of communicating over computer network such as the Internet with a plurality of client devices including client device 14A and other client devices 14B, on which a graphical user interface (GUI) 58 of the estimator program 17 is displayed. In this embodiment, the estimator program 17 may be implemented as a server application and the graphical user interface 58 may be implemented as a native client application or a run-time executable displayed in a web browser, for example. Alternatively, the system 12 may be configured as a single computer system in which the estimator program 17 and graphical user interface 58 are executed and displayed on the same computing device, for example as a single native application running a single thread executed on the processor 16.

#Continuing with FIG. 1, a determination of art investment potential via the computerized art investment estimation system 12 relies on artwork price data 21 stored in a database 22 in the non-volatile memory 20. While database 22 is depicted being stored on the same computing device 14 as the estimator program 17 is executed, it will be appreciated that the database 22 may be implemented on a different computer, such as a separate database server computing device. Artwork price data 21 includes repeat sale pairs of works of art that have been sold and purchased at public auction. The database 22 is configured to be updated to include the latest artwork price data 21 from recent sales, and may be updated continually to ensure the most recently available sales data are contained within the database. The artwork price data 21 includes a first sale price 24 and a second sale price 26 of a plurality of repeat sale pairs 28 of a plurality of works of art associated with an artist. The sales pairs may be associated with the artist due to the artist having created the works of art, for example. As another example, where sales pair data are not sufficiently available for an illiquid artist, the sales pairs may be associated with the artist by being associated with a category or group to which the artist belongs. It will be appreciated that the first sale price may be, for example, an acquisition price paid by an acquirer for a work of art, and the second sale price may be a sale price at which the same acquirer sold the work of art. Alternatively, the second sale price may be a price paid to a subsequent owner of the work of art. Database 22 stores a sale date for each sale price, and thus includes an associated first sale date 24A for the first sale price 24 and an associated second sale date 26A for the second sale price 26, for each of the repeat sale pairs 28. The sales dates 24A and 26A may be used to compute an annualized return for each sale pair 28. Continual updating may include, for example, the database 22 being updated periodically at appropriate intervals, such as at the conclusion of each art auction season with new data of sales of works of art. In the implementations discussed below in relation to FIG. 6, a particular target artist 60A, estimation method 60B, and weights 60C, collectively forming user input 60, may be specified by a user of client device 14A via an artist investment potential tool GUI 58A of the estimator program 17 displayed on GUI 58, where the user is interested in discovering the investment potential of works of art by the specified artist. The weights 60C are referred to as behavioral factors, since they are determined by the behavior of each user, and reflect each user's behavioral approach to investing. The user input 60 is transmitted from the client device 14A to the estimator program 17 of the computing device 14. The computing device 14 processes the user input 60 and returns results 61 for display on the client device 14A. The results 61 may include, for example, a user-specific artist investment potential 64, crowd AIP value 67A, difference score 72, and other artist suggestions 65, as will be explained further below. Other GUIs of tools of the estimator program 17 may also be displayed on the GUI 58, including a preferred artist investment potential tool GUI 58B, a detailed view of which is shown in FIG. 7, an illiquid artists AIP tool GUI 58C, a detailed view of which is shown in FIG. 8, a price prediction tool GUI 58D, a detailed view of which is shown in FIG. 9, and a collection curation tool GUI 58E, a detailed view of which is shown in FIG. 10.