Optimal Combinatorial Electricity Markets

The deregulation of the electricity industry in many countries has created a number of marketplaces in which producers and consumers can operate in order to more effectively manage and meet their energy needs. To this end, this paper develops a new model for electricity retail where end-use customers choose their supplier from competing electricity retailers. The model is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This model prevents strategic bidding and allows the auctioneer to maximise its payoff. Furthermore, we develop optimal single-item and multi-item algorithms for winner determination in such auctions that are significantly less complex than those currently available in the literature

Third-Party Data Providers Ruin Simple Mechanisms

Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism design. When no data provider is present, it has been shown that simple mechanisms are "good enough" -- they can achieve a constant fraction of the revenue of optimal mechanisms. The results in this paper demonstrate that this is no longer true in the presence of a third-party data provider who can provide the bidder with a signal that is correlated with the item type. Specifically, even with a single seller, a single bidder, and a single item of uncertain type for sale, the strategies of pricing each item-type separately (the analog of item pricing for multi-item auctions) and bundling all item-types under a single price (the analog of grand bundling) can both simultaneously be a logarithmic factor worse than the optimal revenue. Further, in the presence of a data provider, item-type partitioning mechanisms---a more general class of mechanisms which divide item-types into disjoint groups and offer prices for each group---still cannot achieve within a $\log \log$ factor of the optimal revenue. Thus, our results highlight that the presence of a data-provider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue

Optimal Auctions when a seller is bound to sell to collusive bidders (new version of "using lotteries ...")

I consider optimal auctions for a seller who is bound to sell a single item to one of two potential buyers, organized in a `well-coordinated' cartel. I show that, even though the seller cannot deter collusion, he can optimally accommodate it by employing a simple mechanism which imposes an inefficient allocation on the bidders unless they pay a sufficiently high amount to avoid it.auctions; optimal auctions; collusion; cartel; mechanism design; auction theory

Double Auctions in Markets for Multiple Kinds of Goods

Motivated by applications such as stock exchanges and spectrum auctions, there is a growing interest in mechanisms for arranging trade in two-sided markets. Existing mechanisms are either not truthful, or do not guarantee an asymptotically-optimal gain-from-trade, or rely on a prior on the traders' valuations, or operate in limited settings such as a single kind of good. We extend the random market-halving technique used in earlier works to markets with multiple kinds of goods, where traders have gross-substitute valuations. We present MIDA: a Multi Item-kind Double-Auction mechanism. It is prior-free, truthful, strongly-budget-balanced, and guarantees near-optimal gain from trade when market sizes of all goods grow to $\infty$ at a similar rate.Comment: Full version of IJCAI-18 paper, with 2 figures. Previous names: "MIDA: A Multi Item-type Double-Auction Mechanism", "A Random-Sampling Double-Auction Mechanism". 10 page

Optimal Release of Inventory Using Online Auctions: The Two Item Case

In this paper we analyze policies for optimally disposing inventory using online auctions. We assume a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a higher expected final price the fewer the number of simultaneous auctions underway. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. We formulate the problem as a discrete time Markov Decision Problem and consider two cases. In the first case we assume the auctions are guaranteed to be successful, while in the second case we assume there is a positive probability that an auction receives no bids. The reason for considering these two cases are that they require different analysis. We derive conditions to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions, and provide several illustration of results. The paper focuses on the two item case which has sufficient complexity to raise challenging questions