TY - JOUR
T1 - Maximizing bidder surplus in simultaneous online art auctions via dynamic forecasting
AU - Dass, Mayukh
AU - Jank, Wolfgang
AU - Shmueli, Galit
PY - 2011/10
Y1 - 2011/10
N2 - This paper presents a novel intelligent bidding system, called SOABER (Simultaneous Online Auction BiddER), which monitors simultaneous online auctions of high-value fine art items. It supports decision-making by maximizing bidders' surpluses and their chances of winning an auction. One key element of the system is a dynamic forecasting model, which incorporates information about the speed of an auction's price movement, as well as the level of competition both within and across auctions. Other elements include a wallet estimator, which gauges the bidders' willingness to pay, and a bid strategizer, which embeds the forecasting model into a fully automated decision system. We illustrate the performance of our intelligent bidding system on an authentic dataset of online art auctions for Indian contemporary art. We compare our system with several simpler ad-hoc approaches, and find it to be more effective in terms of both the extracted surplus and the resulting winning percentage.
AB - This paper presents a novel intelligent bidding system, called SOABER (Simultaneous Online Auction BiddER), which monitors simultaneous online auctions of high-value fine art items. It supports decision-making by maximizing bidders' surpluses and their chances of winning an auction. One key element of the system is a dynamic forecasting model, which incorporates information about the speed of an auction's price movement, as well as the level of competition both within and across auctions. Other elements include a wallet estimator, which gauges the bidders' willingness to pay, and a bid strategizer, which embeds the forecasting model into a fully automated decision system. We illustrate the performance of our intelligent bidding system on an authentic dataset of online art auctions for Indian contemporary art. We compare our system with several simpler ad-hoc approaches, and find it to be more effective in terms of both the extracted surplus and the resulting winning percentage.
KW - Bidder surplus optimization
KW - Dynamic price forecasting
KW - Functional data analysis
KW - Intelligent bidding system
KW - Simultaneous online art auctions
UR - http://www.scopus.com/inward/record.url?scp=80052148666&partnerID=8YFLogxK
U2 - 10.1016/j.ijforecast.2011.01.003
DO - 10.1016/j.ijforecast.2011.01.003
M3 - Article
AN - SCOPUS:80052148666
VL - 27
SP - 1259
EP - 1270
JO - International Journal of Forecasting
JF - International Journal of Forecasting
SN - 0169-2070
IS - 4
ER -