The BARISTA: A Model for Bid Arrivals in Online Auctions

TitleThe BARISTA: A Model for Bid Arrivals in Online Auctions
Publication TypeJournal Article
Year of Publication2007
AuthorsShmueli, G., R. P. Russo, and W. Jank
JournalAnnals of Applied Statistics

The arrival process of bidders and bids in online auctions is important
for studying and modeling supply and demand in the online marketplace.
A popular assumption in the online auction literature is that a Poisson
bidder arrival process is a reasonable approximation. This
approximation underlies theoretical derivations, statistical models and
simulations used in field studies. However, when it comes to the bid
arrivals, empirical research has shown that the process is far from
Poisson, with early bidding and last-moment bids taking place. An
additional feature that has been reported by various authors is an
apparent self-similarity in the bid arrival process. Despite the wide
evidence for the changing bidding intensities and the self-similarity,
there has been no rigorous attempt at developing a model that
adequately approximates bid arrivals and accounts for these features.
The goal of this paper is to introduce a family of distributions that
well-approximate the bid time distribution in hard-close auctions. We
call this the BARISTA process (Bid ARrivals In STAges) because of its
ability to generate different intensities at different stages. We
describe the properties of this model, show how to simulate bid
arrivals from it, and how to use it for estimation and inference. We
illustrate its power and usefulness by fitting simulated and real data
from Finally, we show how a Poisson bidder arrival process
relates to a BARISTA bid arrival process.

Office spreadsheet icon BARISTA datasets.xls1.23 MB

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