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Predicting Online Auction Closing Price Using Grey System Theory
Abstract
Online auctions is a very popular method to buy and sell items on the Internet. However, it is very dynamic in that it is very difficult to predict the winning bid of a given auction. There have been numerous studies to design a bidding strategy that can be utilized by bidders to ensure that they always win an auction. The closing price of an auction is not known and is dependent on several factors such as the number of auctions selling the same item, the number of bidders participating in that auction as well as the behaviour of every individual bidder. To top it up, there can be multiple auctions running concurrently at the same time. To participate in an online auction, one has to decide which auction to participate, how much to bid and when to bid. In most cases, this process is time consuming and does not always guarantee a winning bid. Knowing the closing price would definitely solves part of the problem. If the closing price of an auction is known, then bidder could then decide which auction to participate and at what price. This paper describes one technique to predict the closing price of an auction. This technique is called the Grey System Theory which has been known to be able to accurately predict values in areas where the information is insufficient. This paper also investigates the effectiveness and the accuracy of this theory when applied to online auctions. Some preliminary evaluations will be discussed.
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