Prediction Markets.¶
Wolfers, J., & Zitzewitz, E. (2004). Prediction Markets. Journal of Economic Perspectives, 18(2), 107-126.
Cited by¶
3 citations across 3 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Keynesian Beauty Contest
- The line the two failures draw is worth more than the levers they cost: on this evidence a public signal shortens the recursion when it is scored against a realized outcome, and lengthens it when it merely reports what others chose.
Supported in partVerified against the publisher's abstract
Shows that outcome-settled prediction-market prices aggregate information into accurate forecasts, one half of the contrast, but not its effect on recursion depth.
“market-generated forecasts are typically fairly accurate, and that they outperform most moderately sophisticated benchmarks.”
- The line the two failures draw is worth more than the levers they cost: on this evidence a public signal shortens the recursion when it is scored against a realized outcome, and lengthens it when it merely reports what others chose.
- Precision Weighting
- Machine learning — mixture-of-experts, ensemble averaging weighted by validation performance, attention mechanisms interpreted as soft precision allocation across tokens, uncertainty-aware losses. Organizational decision-making — expert panels weighting members by track record, review boards weighting reviewers by calibration, intelligence assessments weighting sources by reliability ratings. Forecasting and markets — aggregation by historical accuracy or Brier score; prediction markets weighting by capital-at-risk as implicit confidence.
This sourceDescribes aggregation of dispersed information in prediction markets, with capital-at-risk as implicit confidence weighting.
Supported in partVerified against the publisher's abstract
The abstract backs prediction markets aggregating dispersed information into accurate forecasts, but never states capital-at-risk as an implicit confidence weight.
“We analyze the extent to which simple markets can be used to aggregate disperse information into efficient forecasts of uncertain future events.”
- Machine learning — mixture-of-experts, ensemble averaging weighted by validation performance, attention mechanisms interpreted as soft precision allocation across tokens, uncertainty-aware losses. Organizational decision-making — expert panels weighting members by track record, review boards weighting reviewers by calibration, intelligence assessments weighting sources by reliability ratings. Forecasting and markets — aggregation by historical accuracy or Brier score; prediction markets weighting by capital-at-risk as implicit confidence.
- Wisdom of the Crowds
- Prediction markets on elections: A prediction market aggregates thousands of small trades, each reflecting a trader's partial information and private read of the polls, into a single price that tracks the true probability of an outcome better than most named pundits.
This sourceShows that prediction-market prices aggregate dispersed private trader information into accurate forecasts of uncertain events that outperform moderately sophisticated benchmarks, while noting failure modes when trading is thin or correlated.
Supported in partVerified against the publisher's abstract
The abstract backs aggregation of dispersed information into accurate forecasts that beat moderately sophisticated benchmarks, but says nothing of elections, thousands of trades, or beating named pundits.
“we show that market-generated forecasts are typically fairly accurate, and that they outperform most moderately sophisticated benchmarks”
- Prediction markets on elections: A prediction market aggregates thousands of small trades, each reflecting a trader's partial information and private read of the polls, into a single price that tracks the true probability of an outcome better than most named pundits.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 3 of 3 citations: 3 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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