[InTrade is #1 but their software is not yet available for enterprise prediction markets, as I understand it.]
#1. NewsFutures
#2. Inkling Markets
#3. Consensus Point
#4. Zocalo
#5. HSX Research
Source: The Google Search ranking of the “-prediction markets”- webspots…-
External Link: Jed Christiansen’-s review of the software providers of enterprise prediction markets. (I will take a deeper look to it at a later time, and will maybe blog about it.)
This is cross-posted from our Inkling Markets blog where we have far fewer readers than the illustrious Midas Oracle. :)…-
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There are several prediction marketplaces out there for the upcoming U.S. election season and probably more to come. All the ones we know of are intended for participation by the general public. But what if a Presidential campaign ran an internal marketplace? How could prediction markets be used to give a campaign a competitive advantage? We put our political operative hats on for a few minutes and came up with some scenarios:
Resource Allocations
Speaking to veterans of previous presidential campaigns, one of the biggest issues mentioned was building consensus internally on resource allocation across the primaries, then for the general election. Conflicting polling data and infighting among advisors often led to the abandonment of several states where post-mortem analysis of actual voting patterns showed the candidate would have had a chance. Using prediction markets as input to resource allocation decisions, questions could be asked that compare performance metrics across different states, i.e. levels of support among certain voter blocs, predicted endorsements, outcomes of local elections that could impact the general election, etc. This type of information is hard to gather through traditional polling mechanisms but could easily be captured across participants from individual states, locales, and the general campaign.
Fundraising Forecasts
We assume existing forecasting methods used by campaigns are fairly accurate at anticipating how much money will be raised on a quarterly basis from a defined donor list. What may not be as well defined, however, is the impact of various campaign maneuvers on donation levels. For example, a campaign could internally test various scenarios with national campaign staff, field workers, even undecided voters to see if certain activities drive increased fundraising. If the campaign goes through with the activity, the campaign could evaluate the market and pay it out. If not, the market could simply be refunded. Of course, a campaign could also use prediction markets as further input to official forecasts across the different fundraising channels, allowing a more diverse group of people who may have additional insight beyond the “-MBA types”- at campaign headquarters crunching numbers.
Risk Management
(Using Inkling,) questions in a prediction market could be generated by the national campaign and staff at the local level. This “-web of questions”- would be especially useful when trying to anticipate risks to the campaign. The prediction market could be a clearing house of the whispers, rumors, and self-perceived weaknesses of the campaign to continuously test their merit or impact on the campaign. For example, someone from the local staff may be aware of a negative perception the candidate suffers from in a particular voting district. They could run a prediction market about its impacts in an upcoming primary, i.e. “-Will the candidate be perceived as weak on X in analysis of post-appearance local media coverage?”- If the stock price remains low, that issue probably does not need to be dealt with specifically. If it’-s high, it may be an issue the campaign chooses to address proactively ahead of the predicted negative coverage.
Policy Predictions
Given the interest shown to any major candidate, a prediction market gives a campaign an outlet for those supporters wishing to participate in a more meaningful way than simply donating money. A market geared towards public policy across a wide range of issues, both national and local, would be an excellent resource to send people to. Currently most candidate’-s online presence is focused largely on networking, information dissemination, event notifications, and fundraising. A broadly available prediction market would allow people to provide input on what they think will happen from a policy perspective, i.e. will a particular bill pass? How much funding will an initiative receive, etc.? The campaign could then take these predictions as input to shape policy. A similar marketplace could also be set up with a more limited audience of dedicated national and local campaign staff. This marketplace could be augmented with policy experts from around the world to provide additional perspective.
Competitive Analysis
Intended for a tightly controlled group of trusted participants, prediction markets could be run on the performance of the other candidates related to their fundraising levels, endorsements, primary performance, etc. to see how one candidate compares to another. This information would be very useful for strategy formulation. Four years ago some of the candidates tapped the blogosphere to drive early campaign participation and fundraising success.
This year most candidates are trying to build up and leverage their online social networks a la Facebook. Will this campaign season also be the year we see a candidate tapping the collective wisdom of his/her sprawling campaign apparatus?
‘-Are Political Markets Really Superior to Polls as Election Predictors’- is a paper by Robert Erikson and Christopher Wlezian that calls into question whether prediction markets, and specifically IEM, is as accurate as proponents of prediction markets claim. The paper was highlighted here where it was suggested that advocates of prediction markets were turning a blind eye to it.
In the paper the authors show that while when you compare IEM with raw polls, IEM outperforms the polls however when you manipulate the poll data the polls are more accurate. The generate the manipulation the authors looked at poll data from elections from 1952 onwards which show that over time the early leader tends to lose that lead. They then used that relationship to manipulate polls for elections from 1988 onwards and compared the result with the IEM forecasts. The manipulated polls showed a higher level of forecast accuracy.
I think this is an interesting piece of research but it is a stretch to use this to claim that polls are more accurate than prediction markets. The fundamental problem is that when newspapers (or anyone else for that matter) quotes polls, they don’-t refine them using historical data, they quote the actual poll result. If anything the authors have shown a small bias in IEM that one would now expect to get traded out (like the longshot/favorite bias in betting markets or the January effect in financial markets).
Fundamentally, the thing to note is that while polls make prediction markets more accurate, the converse does not hold.
Jed Christiansen at Forbes (just after John Delaney’-s ill-written and pointless comment):
A market effectively aggregates the information from everyone participating. So anything where:
- there is a clear result
- information is dispersed between people and/or locations
- people have an incentive to participate in the market
will likely provide better results than any other forecasting method. Experts just aren’-t as good as they (or anyone else) think they are. It’-s simply better to ask the crowd in these cases.
Missing from Jed Christiansen’-s comment is the emphasis on long series for comparison. Takes time and hundreds of prediction markets to prove the wisdom of crowds.
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UPDATE: Jed Christiansen comments…-
Chris, I agree that for probability assessment, a number of measurements are required to assess success. However, for metrics (ie, sales of widget X, rating of product Y) it doesn’-t require a long series at all. Depending on how poor the current forecasting model is performing, a prediction market could prove successful after just a few measurements.
For a while it seemed like a month wouldn’-t pass without hearing of a new record-breaking art auction, along with the inevitable insinuations of a “-bubble”-. Last night the buyers blinked, as a Van Gogh work expected to command $28-35 million did not get any bids.
People talk about art as an asset class and yet there is no way to sell it short or hedge against declines in value. Clearly, prediction markets are an answer. It seems like this would be a good niche market for a real-money exchange. Markets could either be tied to upcoming auctions or, more likely, an art price index. The latter would allow any art owner a hedge with basis risk.
This, by the way, is not to imply that art prices are about to collapse. There is some evidence that they trail housing prices with a lag of a year or two, but this is mainly anecdotal to the late ’-80s / early ’-90s period. It is more likely that the location of demand is shifting.
Exchanges that are fortunate enough to be operating in modern legal and regulatory regimes show a somewhat limited imagination in their offerings. There are opportunities in the current re-shaping of how art is priced and artists are rewarded.
Previous blog posts by Jason Ruspini:
David Jack is on the right…- (here with Andrew “-Bert”- Black, the BetFair co-founder).
David Jack (Managing Director of TradeFair, a BetFair spin-off)
Previously: Binaries and Spreads: BetFair spins off TradeFair.
NEXT: Why does Tradefair care about Prediction Markets – by TradeFair’-s David Jack – 2007-12-06
John Delaney guides you inside the InTrade prediction markets. (YouTube videos)
#1. Welcome to InTrade
#2. Welcome to Trading 101 – InTrade
#3. Trading 101 on InTrade
Interesting. Well done. I hope we will have much more videos like these from all of the prediction market industry players, in the coming months.
Via “-jwolstenholme”- and via Niall O’-Connor, who got the scoop, here’-s UK-based TradeFair (Binaries and Spreads):
–->- David Jack (Managing Director of TradeFair) —- (Thanks to Niall for the LinkedIn link.)
The New York Times:
[…] Long before political prediction markets sprouted on the Internet, election bets — whether the stakes were money or embarrassing public spectacles — were a ubiquitous part of the American political scene. The practice, which began informally with petty stakes in pool halls in the late 19th century, was by 1900 a multimillion-dollar trade on Wall Street.
In the 1916 contest between Woodrow Wilson and Charles Evans Hughes, about $160 million (in current dollars) was wagered on Wall Street’s outdoor “curb exchange.” By contrast, the 2004 election saw less than $25 million in contracts change hands over the outcome on the Dublin-based InTrade.com market, the largest and most active for-profit market for odds on current American elections. […]
“Until the 1920s, New York would have been the center of gambling in the United States, what Las Vegas is today,” said Paul Rhode, a professor of economic history at the University of North Carolina, Chapel Hill. Technically, gambling on the result of an election was — and is — illegal, but the laws were not widely enforced, and newspapers routinely reported the names of prominent bettors and the Wall Street firms that held the stakes. […]
With the rise of polling in the 1930s and a decline in public approval of political gambling, election betting fell out of favor. The expansion of horse-track betting in 1939, giving people another arena in which to place their bets, also weakened interest in the markets.
Reporters, too, could get political forecasts from increasingly reputable polling agencies. While The New York Herald Tribune still reported on the betting as late as 1940, the odds were relegated to an occasional small paragraph on the financial page, and neither bettors nor stakeholders were named.
The online prediction markets that cropped up around 2000 were less a dot-com revolution than a road back to the earlier form of election coverage.
“In a few years, we may regard the second half of the 20th century as the aberration in which the press used polls rather than markets to track political races,” Justin Wolfers, a business professor at the University of Pennsylvania’s Wharton School, wrote in an e-mail message. “And in the 21st century, we may return to the habits of the early 20th century, reporting on political races through the lens of prediction markets rather than polls.”
Justin Wolfers is right that a new form of journalism may emerge (I call it “-prediction market journalism“-). However, my view is that it will be a minor —-most news media will still be reporting polls rather than prediction market odds.
For an updated version of this document, see the “-paged”- Prediction Markets Timeline.
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CHRONOLOGY &- HISTORY: Prediction Markets Timeline
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Feel free to post a comment or contact me, and I’-ll correct or add a factoid. Thanks.
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#1. Historical Prediction Markets
According to Paul Rhode and Koleman Strumpf, prediction markets almost never got it wrong forecasting the 19 presidential elections that took place from 1868 to 1940. (PDF)
#2. The three Iowa Electronic Markets founders (Robert Forsythe, Forrest Nelson and George Neumann)
“-We ran our first market in 1988. We didn’t have regulatory approval at that point so we were restricted solely to the University of Iowa community. We had under 200 traders and under $5,000.”- –- [Robert Forsythe – PDF file]
– [CFTC’s no-action letter to the IEM – 1992 – PDF file]
– [CFTC’s no-action letter to the IEM – 1993 – PDF file]
#3. Robin Hanson
a) Robin Hanson set up and ran a rudimentary prediction exchange (a market board, PPT file) in January 24, 1989. The outcome to predict was the name of the winner of a Poker party.
b) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange —-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.
Robin Hanson: “-I started a market at Xanadu on cold fusion in April 1989. In May 1990, I started a market there on whether their product would be delivered before Deng died.”-
c) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a bunch of imagination-based prediction markets. See the Murder Mystery Evening described by Barney Pell —-circa June 8, 1989.
d) Until evidence of the contrary, it seems that Robin Hanson was the first to write a paper on prediction markets created and existing primarily because of the information in their prices (as opposed to markets created primarily for speculation and hedging).
Could Gambling Save Science? –- (Reply to Comments) –- by Robin Hanson –- 1990-07-00
Market-Based Foresight: a Proposal –- by Robin Hanson –- 1990-10-30
Idea Futures: Encouraging an Honest Consensus –- (PDF) –- by Robin Hanson –- 1992-11-00
e) Robin Hanson godfathered the Foresight Exchange (created in 1994) and NewsFutures (created in 2000).
f) Robin Hanson invented the concepts of decision markets (PDF) and decision-aid markets.
g) Robin Hanson invented a new market design (for the 2000-2003′-s Policy Analysis Market), the Market Scoring Rules, a mix between CDA and Scoring Rules —-now in use for most enterprise prediction markets and public, play-money prediction exchanges. Note that MSR is mainly used in a one-dimension version, but many researchers are interested in its combinatorial version.
#4. Other Pioneering Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs
a) The Foresight Exchange was founded on September 22, 1994 by Ken Kittlitz, Sean Morgan, Mark James, Greg James, David McFadzean and Duane Hewitt. The Foresight Exchange is a play-money prediction exchange (betting exchange) managed by an open group of volunteers. It pioneered user-created and user-managed, play-money prediction markets. Any person can join the Foresight Exchange and interact with the rest of the Web-based organization. An independent judge (independent from the owner of the claim) should be appointed among the volunteers. [Thus, it’s not “DYI prediction markets”.]
b) The Hollywood Stock Exchange was founded on April 12, 1996, by Max Keiser and Michael Burns. See the patent for the Virtual Specialist. For more info, see: Is HSX the “longest continuously operating prediction market”??? –- REDUX
c) BetFair was founded in 1999 by Andrew Black and Edward Wray, and was launched in England in June 2000. As of today, BetFair is the world’-s biggest prediction exchange (betting exchange, event derivative exchange).
d) NewsFutures was founded in March 2000 and launched in September 2000 in France and in April 2001 in the US by Emile Servan-Shreiber and Maurice Balick. See: NewsFutures Timeline. NewsFutures was the first exchange to let people buy or sell contracts for each side of a binary-outcome event. The advantage of this design is that it avoids the need for “-shorting”-, a notion that tends to confuse novice traders. NewsFutures later extend that approach to deal with n-ary outcome events while implementing automatic arbitrage.
e) TradeSports was launched in Ireland in 2002 by John Delaney. InTrade was later purchased and became a non-sports prediction exchange (betting exchange). As of today, InTrade is the biggest betting exchange on the North-American market —-where betting exchanges are still illegal. As for TradeSports, it closed at the end of 2008, alas.
#5. The Policy Analysis Market Brouhaha
a) Robin Hanson was the main economist behind the 2000–2003 US DoD’-s DARPA’-s IAO’-s FutureMAP–Policy Analysis Market project. (For this project, Robin Hanson invented a new market design, the Market Scoring Rules.) On July 28, 2003, two Democratic US Senators called for the termination of PAM, the the big media gave airtime to their arguments, and the US DOD quickly ended the IAO’-s FutureMAP program.
b) The second branch of the 2000–2003 US DoD’-s DARPA’-s IAO’-s FutureMAP program was handled by the Iowa Electronic Markets and was intended to predict the SARS pandemic. (This project later gave birth to IEM’-s Influenza Prediction Market.)
#6. James Surowiecki’-s The Wisdom Of Crowds
a) James Surowiecki’-s book, The Wisdom Of Crowds, was published in 2004.
b) Impact of The Wisdom Of Crowds.
#7. Recent Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs
a) US-based and US-regulated HedgeStreet was launched in 2004 by John Nafeh, Russell Andersson, and Ursula Burger. A designated contract market (DCM) and a registered derivatives clearing organization (DCO), HedgeStreet is subject to regulatory oversight by the Commodity Futures Trading Commission (CFTC). In November 2006, IG Group bought HedgeStreet for $6 million.
b) Inkling Markets was launched in March 2006 and co-pioneered (with CrowdIQ, which later bellied up) the concept of DIY, play-money prediction markets.
c) In September 2006, TradeSports-InTrade was the first prediction exchange (betting exchange, event futures exchange) to apply Chris Masse’-s concept of X Groups. See: TradeSports-InTrade prediction markets on Bush approval ratings.
d) HubDub was launched in early 2008 and is the second most popular play-money prediction exchange, behind HSX.
#8. Enterprise Prediction Markets
a) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange —-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.
b) In the 1996–-1999 period, HP ran a series of internal prediction markets to forecast the sales of its printers.
c) Eli Lilly sponsored 10 public, industry-level prediction markets in April 2003 (on the NewsFutures prediction exchange).
d) Eli Lilly began using internal prediction markets in February 2004 (powered by NewsFutures).
e) Google‘-s Bo Cowgill published about their use of internal prediction markets in October 2005.
f) Since then, many companies selling software services for enterprise prediction markets have been created.
#9. Disputes Between Traders And Exchanges
a) The scandal of the North Korean Missile prediction market that erupted in July 2006 is, as of today, the biggest scandal that rocked the field of prediction markets.
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