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dc.contributor.authorKarimi, Majid
dc.contributor.authorDimitrov, Stanko 20:19:19 (GMT) 20:19:19 (GMT)
dc.description.abstractWe study market scoring rule (MSR) prediction markets in the presence of risk-averse or risk-seeking agents that have unknown yet bounded risk preferences. It is well known that if agents can be prescreened, then MSRs can be corrected to elicit agents’ beliefs. However, agents cannot always be screened, and instead, an online MSR mechanism is needed. We show that agents’ submitted reports always deviate from their beliefs, unless their beliefs are identical to the current market estimate. This means, in most cases it is impossible for a MSR prediction market to elicit an individual agent’s exact belief. To analyze this issue, we introduce a measure to calculate the deviation between an agent’s reported belief and personal belief. We further derive the necessary and sufficient conditions for a MSR to yield a lower deviation relative to another MSR. We find that the deviation of a MSR prediction market is related to the liquidity provided in the MSR’s corresponding cost-function prediction market. We use the relation between deviation and liquidity to present a systematic approach to help determine the amount of liquidity required for cost-function prediction markets, an activity that up to this point has been described as “art” in the literature.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canadaen
dc.publisherThe Institute for Operations Research and the Management Sciencesen
dc.subjectprobability forecasten
dc.subjectdecision analysisen
dc.subjectprediction marketsen
dc.subjectmarket scoring rulesen
dc.subjectrisk aversionen
dc.subjectcost function market makersen
dc.subjectmarket depthen
dc.subjectmarket liquidityen
dc.titleOn the Road to Making Science of “Art”: Risk Bias in Market Scoring Rulesen
dcterms.bibliographicCitationKarimi, Majid, and Stanko Dimitrov. “On the Road to Making Science of ‘Art’: Risk Bias in Market Scoring Rules.” Decision Analysis 15, no. 2 (May 8, 2018): 72–89.
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Management Sciencesen

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