A Simulation-Based Model for Final Price Prediction in Online Auctions

Online auctions, a profitable, exciting, and dynamic part of e-commerce, have enjoyed increasing public interest. However, there is still a paucity of literature on final price prediction for online auctions. Although Markov process models provide a mathematical approach to predicting online auction prices, estimating parameters of a Markov process model in practice is a challenging task. In this paper we propose a simulation-based model as an alternative approach to predicting the final price in online auctions. The simulation results show that the proposed model can predict the final price more accurately than a Markov process model. Additionally, the consistent lower predictions of the Markov process model suggest a direction for future research into improving performance in both models.