Efficient Market Making via Convex Optimization, and a Connection to Online Learning

Abstract

We propose a general framework for the design of securities markets over combinatorial or infinite state or outcome spaces. The framework enables the design of computationally efficient markets tailored to an arbitrary, yet relatively small, space of securities with bounded payoff. We prove that any market satisfying a set of intuitive conditions must price… (More)
DOI: 10.1145/2465769.2465777

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