Agents for Predicting Online Auction Closing Prices

Deborah Lim and Patricia Anthony and Ho, Chong Mun (2008) Agents for Predicting Online Auction Closing Prices. pp. 32-44.

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Abstract

Auction markets provide centralized procedures for the exposure of purchase and sale orders to all market participants simultaneously. Online auctions have effectively created a large marketplace for participants to bid and sell products and services over the Internet. eBay pioneered the online auction in 1995. As the number of demand for online auction increases, the process of monitoring multiple auction houses, picking which auction to participate in, and making the right bid become a challenging task for the consumers. Hence, knowing the closing price of a given auction would be an advantage since this information will be useful and can be used to ensure a win in a given auction. However, predicting a closing price for an auction is not easy since it is dependent on many factors. This paper reports on a predictor agent that utilises the Grey System Theory to predict the closing price for a given auction. The performance of this predictor agent is compared with another well known technique which is the Artificial Neural Network. The effectiveness of these models is evaluated in a simulated auction environment.

Item Type:	Chapter In Book
Keyword:	Online Auction , Grey System Theory , Artificial Neural Network
Subjects:	H Social Sciences > HF Commerce > HF1-6182 Commerce > HF5001-6182 Business > HF5469.7-5481 Markets. Fairs
Department:	FACULTY > Faculty of Food Science and Nutrition
Depositing User:	NORAINI LABUK -
Date Deposited:	22 Dec 2021 16:29
Last Modified:	22 Dec 2021 16:29
URI:	https://eprints.ums.edu.my/id/eprint/29690

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