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A Family of Growth Models for Representing the Price Process in Online Auctions (2007)
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@MISC{Hyde07afamily,
author = {Valerie Hyde and Wolfgang Jank and Galit Shmueli},
title = {A Family of Growth Models for Representing the Price Process in Online Auctions},
year = {2007}
}
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Abstract
Bids during an online auction arrive at unequally-spaced discrete time points. Our goal is to cap-ture the entire continuous price-evolution function by representing it as a functional object. Various nonparametric smoothing methods exist to recover the functional object from the observed discrete bid data. Previous studies use penalized polynomial and monotone smoothing splines; however, these require the determination of a large number of coefficients and often lengthy computational time. We present a family of parametric growth curves that describe the price-evolution during online auctions. Our approach is parsimonious and has an appealing interpretation in the online auction context. We also provide an automated fitting algorithm that is computationally fast. Our method is illustrated on several eBay datasets. ∗Author names are listed in alphabetical order. † This paper is part of the Doctoral Dissertation of the first author. 1 1
Keyphrases
online auction growth model price process functional object lengthy computational time doctoral dissertation first author previous study observed discrete bid data entire continuous price-evolution function several ebay datasets unequally-spaced discrete time point alphabetical order online auction context monotone smoothing spline large number online auction arrive parametric growth curve author name automated fitting algorithm
