Abstract
In this paper we study the design and characterization of prediction markets in the presence of traders with unknown risk-aversion. We formulate a series of desirable properties for any “market-like” forecasting mechanism. We present a randomized mechanism that satisfies all these properties while guaranteeing that it is myopically optimal for each trader to trade honestly, regardless of her degree of risk aversion. We observe, however, that the mechanism has an undesirable side effect: the traders’ expected reward, normalized against the inherent value of their private information, decreases exponentially with the number of traders. We prove that this is unavoidable: any mechanism that is myopically strategyproof for traders of all risk types, while also satisfying other natural properties of “market-like” mechanisms, must sometimes result in a player getting an exponentially small normalized expected reward.
This work was supported by the National Science Foundation under award CCF-0728768. The proofs have been omitted from this short paper; the extended version can be found at http://www.umich.edu/~rsami/papers/RiskAverseMarkets.pdf [7]
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Dimitrov, S., Sami, R., Epelman, M. (2009). Subsidized Prediction Markets for Risk Averse Traders. In: Leonardi, S. (eds) Internet and Network Economics. WINE 2009. Lecture Notes in Computer Science, vol 5929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10841-9_47
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DOI: https://doi.org/10.1007/978-3-642-10841-9_47
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