Practically Efficient Secure Single-Commodity Multi-market Auctions

We study the problem of securely building single-commodity multi-markets auction mechanisms. We introduce a novel greedy algorithm and its corresponding privacy preserving implementation using secure multi-party computation. More specifically, we determine the quantity of supply and demand bids maximizing welfare. Each bid is attached to a specific market, but exchanges between different markets are allowed up to some upper limit. The general goal is for the players to bid their intended valuations without concerns about what the other players can learn. This problem is inspired by day-ahead electricity markets where there are substantial transmission capacity between the different markets, but applies to other commodity markets like gas. Furthermore, we provide computational results with a specific C++ implementation of our algorithm and the necessary MPC primitives. We can solve problems of 1945 bids and 4 markets in 1280 seconds when online/offline phases are considered. Finally, we report on possible set-ups, workload distributions and possible trade-offs for real-life applications of our results based on this experimentation and prototyping.