Abstract
The rule with which automated computerised auctions are closed play an important role in determining bidder strategies and auction outcomes. In this paper we examine two such rules: auctions with randomised closing times and fixed deadlines. To this end, stochastic models of auctions with discrete state-space representing the prices attained are developed and analysed. The models allow us to determine the stationary probabilistic outcomes of the auctions, which are used to examine the bidder performance, measured as the savings it makes with respect to the maximum payable or its payoff. For this purpose, one bidder is singled out as the “special bidder” (SB) and its performance is studied as a function of the speed with which it raises the price, or its bid rate. The results show that with random closures, the SB has incentives to place bids promptly to obtain high savings; on the other hand, with fixed deadline auctions, the SB should choose its bid rate with respect to the other system parameters in order to maximise payoffs.
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References
Roth, A., Ockenfels, A.: Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet. Amer. Econ. Rev. 92(4), 1093–1103 (2002)
Ariely, D., Ockenfels, A., Roth, A.: An experimental analysis of ending rules in Internet auctions. RAND Journal of Economics 36(4), 890–907 (2005)
Ockenfels, A., Roth, A.E.: Late and multiple bidding in second price Internet auctions: Theory and evidence concerning different rules for ending an auction. Games Econ. Behav. 55(2), 297–320 (2006)
LSE: London Stock Exchange: Market Enhancements, http://www.londonstockexchange.com/information-providers/technical-library/technical-guidance-notes/technicalguidancenotesarchive/release.pdf (accessed on January 28, 2010)
Velan, K.: Modelling Bidders in Sequential Automated Auctions. The Computer Journal 53(2), 208–218 (2010)
Gelenbe, E., Velan, K.: An Approximate Model for Bidders in Sequential Automated Auctions. In: Håkansson, A., Nguyen, N.T., Hartung, R.L., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2009. LNCS(LNAI), vol. 5559, pp. 70–79. Springer, Heidelberg (2009)
Gelenbe, E.: Analysis of Automated Auctions. In: Levi, A., Savaş, E., Yenigün, H., Balcısoy, S., Saygın, Y. (eds.) ISCIS 2006. LNCS, vol. 4263, pp. 1–12. Springer, Heidelberg (2006)
Gelenbe, E.: Analysis of Single and Networked Auctions. ACM Trans. Internet Technol. 9(2), 1–24 (2009)
Medhi, J.: Stochastic Processes, 2nd edn. Wiley Eastern Ltd., Chichester (1994)
Gelenbe, E., Györfi, L.: Performance of Auctions and Sealed Bids. In: Bradley, J.T. (ed.) EPEW 2009. LNCS, vol. 5652, pp. 30–43. Springer, Heidelberg (2009)
Onur, I., Tomak, K.: Impact of ending rules in online auctions: The case of Yahoo.com. Decision Support Systems 42(3), 1835–1842 (2006)
Rothkopf, M.H., Harstad, R.M.: Modeling Competitive Bidding: A Critical Essay. Manage. Sci. 40(3), 364–384 (1994)
Rothkopf, M.H.: Decision Analysis: The Right Tool for Auctions. Decision Analysis 4(3), 167–172 (2007)
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Velan, K., Gelenbe, E. (2010). Analysing Bidder Performance in Randomised and Fixed-Deadline Automated Auctions. In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2010. Lecture Notes in Computer Science(), vol 6071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13541-5_5
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DOI: https://doi.org/10.1007/978-3-642-13541-5_5
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