Notes from Wolfers and Zitzewitz paper on Prediction Markets

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Here are my notes on the paper, Prediction Markets, by Justin Wolfers and Eric Zitzewitz

Accuracy
Wolfers and Zitzewitz recently published Interpreting Prediction Market Prices as Probabilities that claims that “prediction market prices are usually close to the mean beliefs of traders” and concludes…

with some guidance for practitioners. In most cases we find that prediction market prices aggregate beliefs very well. Thus, if traders are typically well-informed, prediction market prices will aggregate information into useful forecasts. The efficacy of these forecasts may however be undermined somewhat for prices close to $0 or $1, when the distribution of beliefs is either especially disperse, or when trading volumes are somehow constrained, or motivated by an unusual degree of risk-acceptance.

Limitations

Thin Markets

…the HP (forecasting printer sales) and Siemens (predicting delivery of sofware on schedule) experiences suggested that motivating employees to trade was a major challenge. In each case, the firms ran real money exchanges, with only a relatively small trading population (20-60 people), and subsidized participation in the market, by either endowing traders with a portfolio or matching initial deposits. The predictive performance of even these very thin markets was quite striking.

Possibilities for Arbitrage

Prediction markets appear to present few opportunities for arbitrage.

Gaming the Market

In most cases, the time series of prices in these markets does not appear to follow a predictable path and simple betting strategies based on past prices appear to yield no profit opportunities.


 Small Probablility Events

People tend to overvalue small probabilities and undervalue near certainties (The “volatility smile” in options refers to a related pattern in financial markets.) It is likely that prediction markets will also perform poorly at predicting small probability events.
Another behavioral bias reflects the tendency of market participants to trade according to their desires, rather than their objective probability assessments. …as long as marginal trades are motivated by profits rather than partisanship, prices will reflect the assessments of (unbiased) profit motive.

Criteria for Success
For a prediction market to work well
1. Contracts must be clear, easily understood, and easily adjudicated.
2. A motivation to trade must exist. Perhaps simply through the thrill of pitting one’s judgment against others
3. There must be some disagreement about likely outcomes. “Disagreement is unlikely among fully rational traders with common priors. It is more likely to occur when traders are overconfident in the quality of their private information or in their ability to process public information or when they have priors that are sufficiently different to allow them to agree to disagree.”
4. There must be useful intelligence to aggregate. Public information cannot be selective, inaccurate, or misleading.

Types of contracts
All contracts assume risk neutrality – that risk doesn’t affect investors’ decisions becuase the amounts being wagered are small.

Winner-takes-all: contract pays off if and only if a specific event occurs. The price on a winner-take-all market represents the market’s expectation of the probability that an event will occur.

Index: contract pays off an amount that varies based on a numeric outcome, say, the percentage of  the popular vote or the number of printers sold. The contract price represents the mean value that the market assigns to the outcome.

“Spread” betting: traders bid on the cutoff that determines whether an event occurs, like point-spread betting in football, where the bet is either that one team will win by at least a certain number of points, or will not. The price of the bet is fixed, but the size of the spread can adjust. When spread betting is combined with an even-money bet (that is, winners double their money while losers receive zero), the outcome can yield the market’s expectation of the median outcome because this is only a fair bet if a payoff is as likely to occur as not.

Families of winner-takes-all contracts can reveal the probability distribution of the market’s expectations.

Written by

glen.mohr
Since 2001, Glen has designed and managed professional development programs that develop leaders and deliver innovative solutions simultaneously. Clients, including Citigroup (11 years), Merrill Lynch (5 years), and PNC (2 years), consistently achieve the goals of more self-aware and capable leaders, ongoing organizational capacity for innovation, and innovative solutions to client needs - of which a high percentage move forward to generate revenue. He has personally coached hundreds of teams and has recruited and trained a team of expert coaches. He holds a Masters from Harvard with a concentration in Technology in Education and a BS in Architecture from the University of Virginia.

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