Optimal minimum bids and inventory scrapping in sequential, single-unit, Vickrey auctions with demand learning

Keyphrases

• Approximation Methods 20%
• Auction Design 20%
• Bayesian Markov Decision Process 20%
• Bidders 20%
• Certainty Equivalent Control 40%
• Clairvoyance 20%
• Control Function 20%
• Demand Distribution 20%
• Design Problems 20%
• Dynamic Auctions 20%
• Exact Solutions 20%
• First-order Necessary Conditions 20%
• Gamma Mixture 20%
• Gamma Prior 20%
• Inventory Cost 20%
• Learning Demand 100%
• Marginal Profit 20%
• Market Response 20%
• Markov Decision Process 20%
• Multi-unit Auctions 40%
• Number of Bidders 20%
• Numerical Experiments 20%
• Poisson 20%
• Q-function Approximation 40%
• Retailers 20%
• Riley 20%
• Samuelson 20%
• Scrap 100%
• Seller 100%
• Single Unit 100%
• Structured Value Iteration 20%
• Value Iteration 20%
• Vickrey Auction 100%
• Virtual Values 40%

Mathematics

• Approximation Function 100%
• Bayesian 50%
• Markov Decision Process 100%
• Necessary Condition 100%
• Numerical Experiment 50%