|
||||
|
||||
Modeling Bid Arrivals in Online Auctions
Galit Shmueli University of Maryland - Department of Decision, Operations & Information Technologies Ralph P. Russo University of Iowa - Department of Statistics & Actuarial Science Wolfgang Jank University of Maryland - Decision and Information Technologies Department 2004 Robert H. Smith School Research Paper No. RHS-06-001 Abstract: Summary.We introduce a new family of non-homogeneous Poisson processes (NHPP) that are useful for modeling pure and contaminated self-similar processes which describe arrivals within a finite time period. Our motivation comes from the bid arrival process in online auctions. Modeling bid arrivals in online auctions is challenging since bidding dynamics change over the course of the auction. While the start of the auction typically sees an unusual amount of early bidding which is followed by a period of little activity, the auction end typically experiences an enormous amount of last minute bidding, also known as sniping. This observed heterogeneity in bidding dynamics commands a very flexible class of models. We address these modeling challenges by proposing a class of 3-stage non-homogenous Poisson processes. We investigate the probabilistic and statistical properties of these models and illustrate their usefulness for fitting and interpreting real data from eBay.com.
Keywords: Non-homogenous Poisson process,online auction,bid data, self-similarity, bidding dynamics Working Paper SeriesDate posted: May 17, 2006 ; Last revised: May 17, 2006Suggested CitationContact Information
|
|
||||||||||||||||||||||||
© 2009 Social Science Electronic Publishing, Inc. All Rights Reserved. Terms of Use Privacy Policy
This page was served by apollo4 in 0.110 seconds.