Abstract:
A method for extracting an implied value of a component associated with a plurality of product packages is disclosed. One embodiment of the method includes receiving data associated with a plurality of product packages. It is noted that the data comprises product package price data associated with the plurality of product packages. The data is processed utilizing a mathematical optimization to produce first output data. The first output data is processed with a statistical regression to produce second output data. The second output data includes an estimated value and its standard error of a component associated with the plurality of product packages.
Abstract:
The present invention provides an automated estimation and optimization solution for selecting the optimal bid for an item in an auction. The characteristics of the auction are selected (e.g., auction format, reserve price). A relevant bidding model, based on the characteristics of the auction, is selected. The structure of the auction is estimated based on the relevant bidding model. A bid function is determined based on the auction structure and user inputs regarding the item being bid on and the characteristics of the rival bidders. An optimal bid is determined based on the bid function and user-defined evaluation criterion. An embodiment of the present invention provides a method and system that determines the latent elements of the auction environment taking into account the strategic and information conditions with minimal assumptions on the distributions of unobserved random elements. The present invention allows a bidder to estimate the unobservable private signals of rival bidders and to determine the optimal bid the bidder can employ to optimize their evaluation criterion.
Abstract:
A method and system for selecting feedback rules for an online auction. An exemplary method may comprise controlling feedback by customizing feedback rules for an online auction substantially no earlier than entry of auction rules into an auction program by an end-user, storing the customized feedback rules for future use by the auction program, and conducting the online auction by the auction program using the feedback rules.
Abstract:
A computer-implemented method for automatic contract monitoring. An electronic version of a contract comprising at least one term and at least one penalty is received. Information relevant to enforcement of contract is monitored. A transaction related to the contract is received. Using the information, it is automatically determined whether the transaction is compliant with the contract.
Abstract:
A method and associated system comprise obtaining historical auction data, determining, from the historical auction data, a first parameter that is a function of a joint bid distribution and a density function related to the joint bid distribution, selecting a bidder, obtaining a value distribution for the selected bidder, and solving an equation. The equation may include the first parameter and the selected bidder's value distribution, and not the value distribution of other bidders. The equation computes a bid value associated with the selected bidder for a given bid.
Abstract:
A computer-implemented method for estimating bidder valuation. A probability that a bid of a first bidder in an auction is not greater than a first value is determined, wherein a second bidder has a valuation in the auction equal to a second value. A rate at which the probability changes is determined. The ratio of the probability to the rate of change is determined. The ratio is added to the rival bid to determine an estimate of the first bidder's valuation.
Abstract:
A method of computing at least one solution to an auction winner-determination problem includes receiving a plurality of bids in an auction and computing at least one solution to an auction winner-determination problem for the auction using the plurality of bids.
Abstract:
An embodiment in accordance with the present invention provides a method for determining a demand function for an item. For example, the method includes determining a first estimate of the demand function for the item by utilizing a first auction having a first set of auction parameters. Additionally, the method includes determining a second estimate of the demand function for the item by utilizing a second auction using auction data from the first auction. The second auction has a second set of auction parameters based on the first estimate of the demand function.
Abstract:
A computer-implemented automated decision support system for designing an auction for a given item includes a structure extractor that estimates unknown elements of market structure of the auction based on auction characteristics data extracted from historical auctions for similar items and a bidding model matching the extracted auction characteristics data. The decision support system also includes a bidding behavior predictor that predicts bidding behaviors of bidders in the auction based on the estimated unknown elements of market structure and characteristics of the auction. In addition, the system includes an optimizer that employs an evaluation criterion to generate an evaluation of the auction based on (1) the estimated unknown elements of market structure and (2) the predicted bidding behavior of bidders. A method of providing an automated auction analysis is also described.
Abstract:
An automated estimation and optimization solution for selecting the best auction format by determining the latent elements of the auction environment taking into account the strategic and information conditions with minimal assumptions on the distributions of unobserved random elements. Structural analysis of bid data from prior auctions is used to identify and estimate the distributions of bidders' private signals conditional on observable bidder characteristics. The estimated signal distributions, identified by the structural analysis, are used to evaluate alternative auction formats and to select the best format from among a given set of candidates. The present invention provides decision support tools to select an auction format based on structural econometric analysis of available data on the market environment. A decision-maker may estimate the unobservable private signals of the bidders and to determine the best auction format the decision maker can employ to sell a given set of items.