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Johannes C. Müller

Publications and source records attributed to Johannes C. Müller.

3 recordsLinked to original sources

Pricing and clearing combinatorial markets with singleton and swap orders: Efficient algorithms for the futures opening auction problem

In this article we consider combinatorial markets with valuations only for singletons and pairs of buy/sell-orders for swapping two items in equal quantity. We provide an algorithm that permits polynomial time market-clearing and -pricing. The results are presented in the context of our main application: the futures opening auction problem. Futures contracts are an important tool to mitigate market risk and counterparty credit risk. In futures markets these contracts can be traded with varying expiration dates and underlyings. A common hedging strategy is to roll positions forward into the next expiration date, however this strategy comes with significant operational risk. To address this risk, exchanges started to offer so-called futures contract combinations, which allow the traders for swapping two futures contracts with different expiration dates or for swapping two futures contracts with different underlyings. In theory, the price is in both cases the difference of the two involved futures contracts. However, in particular in the opening auctions price inefficiencies often occur due to suboptimal clearing, leading to potential arbitrage opportunities. We present a minimum cost flow formulation of the futures opening auction problem that guarantees consistent prices. The core ideas are to model orders as arcs in a network, to enforce the equilibrium conditions with the help of two hierarchical objectives, and to combine these objectives into a single weighted objective while preserving the price information of dual optimal solutions. The resulting optimization problem can be solved in polynomial time and computational tests establish an empirical performance suitable for production environments.

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Strict linear prices in non-convex European day-ahead electricity markets

The European power grid can be divided into several market areas where the price of electricity is determined in a day-ahead auction. Market participants can provide continuous hourly bid curves and combinatorial bids with associated quantities given the prices. The goal of our auction is to maximize the economic surplus of all participants subject to quantity constraints and price constraints. The price constraints ensure that no one incurs a loss. Only traders who submitted a combinatorial bid might miss a not-realized profit. The resulting problem is a large scale mathematical program with equilibrium constraints (MPEC) and binary variables that cannot be solved efficiently by standard solvers. We present an exact algorithm and a fast heuristic for this type of problem. Both algorithms decompose the MPEC into a master problem (a MIQP) and pricing subproblems (LPs). The modeling technique and the algorithms are applicable to a wide variety of combinatorial auctions that are based on mixed integer programs.

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Competitive Equilibrium Relaxations in General Auctions

The goal of an auction is to determine commodity prices such that all participants are perfectly happy. Such a solution is called a competitive equilibrium and does not exist in general. For this reason we are interested in solutions which are similar to a competitive equilibrium. The article introduces two relaxations of a competitive equilibrium for general auctions. Both relaxations determine one price per commodity by solving a difficult non-convex optimization problem. The first model is a mathematical program with equilibrium constraints (MPEC), which ensures that each participant is either perfectly happy or his bid is rejected. An exact algorithm and a heuristic are provided for this model. The second model is a relaxation of the first one and only ensures that no participant incurs a loss. In an optimal solution to the second model, no participant can be made better off without making another one worse off.

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