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InTrades global warming prediction markets are more socially interesting than BetFairs ones.

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InTrade has just opened (and not publicized yet on their site feed) a set of global warming prediction markets &#8212-more exactly, event derivative markets on whether the world&#8217-s biggest national governments will soon agree to reduce CO2 emissions under the UNFCCC treaty. They are, in my view, more interesting than the pitiful BetFair&#8217-s prediction markets on global warming (2 out of 3, I mean) for the same two reasons (but which work positively, this time):

  1. Uninformed traders will be able to trade their opinions. Most of the US citizens have an opinion (positive or negative) on the US Congress politics and the federal legislations.
  2. Informed traders (hopefully, the market makers) will be able to follow some advanced indicators (in the Washington D.C. media, for instance) pertaining to this upcoming legislation (if any).

Once again, it shows that John Delaney&#8217-s InTrade is the King of the Prediction Markets &#8212-and that BetFair-TradeFair is painfully playing catch-up.

Here&#8217-s the InTrade contract statement for the US &#8212- (USA agrees before end of 2009 to reduce CO2 emissions by 10% or more by year 2025):

A contract will settle (expire) at 100 ($10.00) if the United States agrees before the end of 2009 to reduce CO2 emissions by the amount specified in the contract by the year 2025 (relative to the 1990 emissions baseline).

A contract will settle (expire) at 0 ($0.00) if the United States DOES NOT agree before the end of 2009 to reduce CO2 emissions by the amount specified in the contract by the year 2025 (relative to the 1990 emissions baseline).

Any reduction target must be part of a United Nations Framework Convention on Climate Change (UNFCC) [*] agreement reached before the end of 2009. Any agreement to reduce CO2 emissions made outside of the UNFCC will not be considered for expiry purposes.

A reduction target does not have to be ratified for the contracts to be expired – only agreed to under the UNFCC. [*]

Expiry will be based on official and public announcements from US officials or the UNFCC Secretariat, as reported in three independent and reliable media sources.

Due to the nature of this contract please also see Contract Rule 1.7 Unforeseen Circumstances.

The Exchange reserves the right to invoke Contract Rule 1.8 (Time Protection) if deemed appropriate.

Any changes to the result after the contract has expired will not be taken into account – Exchange Rule 1.4

Please contact the exchange by emailing [email protected] if you have any questions regarding this contract before you place a trade.

Important:
Please contact the Exchange if you have any query or uncertainty (including how it may be settled) about this Contract, the Rule above or the Contract Rules before you trade.

There are 4 other contracts (E.U., Russia, Japan, and China+India).

[*] There are 3 &#8220-C&#8221-s actually. Those Irish bozos are not even able to spell it correctly. &#8211-&gt- UNFCCC (United Nations Framework Convention on Climate Change). Look at the logo, below.

UNFCCC (United Nations Framework Convention on Climate Change)

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UPDATE: Mike Linksvayer&#8217-s comment&#8230-

They’d be even more interesting if offered in combination with electoral outcomes and more yet if offered in combination with climate outcomes. I’m happy to see BINLADEN+MUSHARRAF contracts recently added, but volume is almost nil. Intrade (or someone new) will need better technology to be really socially interesting — be a source of many contingent probabilities. Many explicit combination contracts is just unworkable. I’m also happy to see Intrade offering several multi-year contracts, of which the climate ones are a good example. I believe the Google Lunar contract is currently the longest term one, expiring in 2012. I’m rooting for Intrade and for something better to come along, simultaneously. :)

UPDATE #2: I have just found out, this Sunday afternoon, thanks to a tip from Ralf Martin, that the InTrade global warming prediction markets were set up in collaboration with the London School of Economics&#8217- Centre for Economic Perfomance.

UPDATE #3: InTrade have corrected the spelling on Saturday, December 15, 2007.

NEXT: The London School of Economics chose InTrade-TradeSports over BetFair-TradeFair for floating event derivatives on global warming.

Previous blog posts by Chris F. Masse:

  • Since YooPick opened their door, Midas Oracle has been getting, daily, 2 or 3 dozens referrals from FaceBook.
  • US presidential hopeful John McCain hates the Midas Oracle bloggers.
  • If you have tried to contact Chris Masse thru the Midas Oracle Contact Form, I’m terribly sorry to inform you that your message was not delivered to the recipient.
  • THE CFTC’s SECRET AGENDA —UNVEILED.
  • “Over a ten-year period commencing on January 1, 2008, and ending on December 31, 2017, the S & P 500 will outperform a portfolio of funds of hedge funds, when performance is measured on a basis net of fees, costs and expenses.”
  • Meet professor Thomas W. Malone (on the right), from the MIT’s Center for Collective Intelligence.
  • Tom W. Bell rebuts the puritan and sterile petition organized by the American Enterprise Institute (which has on its payroll Paul Wolfowitz, the bright masterminder of the Iraq war).

Why does Tradefair care about Prediction Markets

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Are prediction markets good at providing a true measure of probability?

Crowd theory says yes, business interests may complicate things.

How is accuracy obtained?

Well of course the answer is obvious – if you want an accurate measure of probability look at the fundamentals for yourself and then ask a lot of people for their opinion. If you encourage the participants to put either reputation and/or money at risk their prediction skills get better. If you provide a platform where systems can participate as well as individuals then not only is the best assessment of probability obtained but it becomes highly dynamic and shifts with every small change in the underlying markets/world conditions.

Sounds complicated, but what does this mean for a business?

Well, simply build an exchange that can provide unprecedented capacity and let the world decide what the likelihood is of an event happening.

And who are Tradefair?

Tradefair is Betfair&#8217-s new home for the financial bettor and trader – our binaries exchange product has opened with straightforward traditional financial markets (FTSE up/down) but one of the things that excites us hugely is the inclusion of market types such as Interest Rates. We call these the &#8220-unhedgeables&#8221-, markets that we all have an opinion on, all understand some of the fundamentals but don&#8217-t have the safety net of an underlying market to hedge into. We are starting in a modest way but we firmly believe that the ONLY place that true market sentiment can be measured is on an exchange.

Why does Tradefair care about prediction markets?

Take a look at Betfair today – it has some of the most liquid, volatile and high participation prediction markets in the world. Participation drives the price down and provides fantastic value to our customers. This has allowed us to build a business that we are all really proud of. The Tradefair team believe that by focusing on financial markets, delivering exchange technology that allows mass participation in an accessible, highly available and transparent manner will allow us bring that same value proposition to the financial sector.

Slate publishes a BetFair explainer for the Americans.

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YouBet – The wonders and dangers of online sports wagering. – (page 2) – [BetFair explained to the Americans] – by Slate&#8217-s T.D. Thornton – 2007-11-28

[…] Betfair, which opened for business in 2000, is best described as day trading for sports bettors. Using Web-based accounts, anonymous users can set their own odds or bid on odds offered by other players. Online &#8220-betting exchanges&#8220-—there are dozens, but Betfair is the kingpin, with a 90 percent market share—eliminate the role of odds-setting middlemen like local bookies and Las Vegas sports books. Instead of wagering on take-it-or-leave-it odds set by the house, gamblers are free to choose among many different price points, striking bets for as little as $1 up to hundreds of thousands. […]

On balance, Betfair offers a number of advantages over traditional sports betting. Compared with bookies and casinos, exchanges keep a much smaller cut of the action, a 1 percent to 3 percent &#8220-vig&#8221- that&#8217-s far less than the standard 10 percent. (In the long run, the exchanges are banking on greater betting volume far outpacing the difference in price: Betfair handles 5 million transactions a day, processing more than 300 bets per second.) […]

Exchanges are also unique in that you can lay odds on a team or individual to lose a sporting event. Naysayers believe that betting to lose is, well, unsporting, and that it is an open invitation for corruption and skullduggery. But this argument is idealistic whitewash. Just ask anyone involved in high finance, where betting to lose is an accepted, ethical strategy—on Wall Street, it&#8217-s called short selling. […]

The most clever innovation, however, is in-game gambling. No longer must you stop placing bets once the game begins. In-game wagering lends itself best to slower-paced sports like golf. When the action is much faster, the limits of technology get pushed to ridiculous proportions, with frantic players punching in frenzied bets that have more to do with market timing than sports. […]

If the United States loosened up its regulations, online exchanges would proliferate here. By creating a market-based framework for stateside sports betting, a chaotic gambling scene would, for once, have some order and credibility. […]

#1. This is the most significant news piece about BetFair I have seen in the American media.

#2. You&#8217-ll have noted that the prediction market approach is completely absent from the writer&#8217-s angle. (TradeSports and InTrade are not even cited.) My view is that this betting exchange approach and our prediction market approach are complementary. BetFair should have both.

Could a political campaign use prediction markets?

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This is cross-posted from our Inkling Markets blog where we have far fewer readers than the illustrious Midas Oracle. :)&#8230-

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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 &#8220-MBA types&#8221- 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 &#8220-web of questions&#8221- 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. &#8220-Will the candidate be perceived as weak on X in analysis of post-appearance local media coverage?&#8221- If the stock price remains low, that issue probably does not need to be dealt with specifically. If it&#8217-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&#8217-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?

Separating cheap talk from truly held beliefs

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Plight of the Fortune Tellers: Why We Need to Manage Financial Risk Differently

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In his book, Plight of the Fortune Tellers, Riccardo Rebonato describes how an invitation to bet can be used to separate cheap talk from truly held beliefs (and, in the process, ruin an otherwise engaging dinner conversation).

In the early to mid 1990s in the United Kingdom and in other European countries a widespread fear developed that a variant form of CJD might spread to humans. CJD is a fatal illness—also know as “mad cow disease”—that is well-known to affect bovines. The variant form was thought to have contaminated human beings via the ingestion of beef from cattle affected by the disease. … When the first human cases appeared scientists did not know whether they were observing the tip of an iceberg or whether the relatively few observed cases, tragic as they were, constituted a rather limited and circumscribed occurrence. “Expert scientists” were soon willing to go on record with statements to the effect that “it could not be excluded” that a catastrophe was unfolding. The nonscientific press was all too eager to jump on the bandwagon, and extravagant claims were soon presented, such as that hundreds of thousands, or perhaps even millions, of lives could be lost over the next decade. Specific probabilities were not stated, but the prominence of the reporting only made sense if the possibility of this catastrophic event was nonnegligible: the newspapers, at least judging by the inches of column space devoted to the topic, were not talking about a risk as remote as being hit by a meteorite.

As the months went by … the number of cases did not significantly increase…. Looking at the data available at the time with a statistical eye, I was becoming increasingly convinced that the magnitude of the potential effect was being greatly exaggerated. At just the same time, a well-educated, but nonscientist, friend of mine (a university lecturer) was visiting London and we decided to meet for dinner. As the conversation moved from one topic to another, he expressed a strong belief, formed by reading the nonscientific press, that the spread of CJD would be a major catastrophe for the U.K. population in the next five to ten years. He was convinced, he claimed, that “hundreds of thousands of people” would succumb to the disease. … I challenged him to enter a bet, to be settled in ten years’ time, that the number of occurrences would not be consistent with a major epidemic. My friend refused to take me up on my offer, despite my very attractive odds (attractive, that is, given his stated subjective probabilities). He claimed that “one does not bet on these things”- that he found my proposal distasteful- that, anyhow, he was not a betting man- and so on. I explained that I was not trying to gain material advantage from a possible human disaster, but I was simply probing the strength of his convictions on the matter. Ultimately, the bet was not entered, and the evening was rather spoiled by my proposal.

Julian Simon’s bet with Paul Erhlich is perhaps the most famous example of the use of a bet to test the strength of convictions. Robin Hanson has done a substantial amount of work on the foundations of such &#8220-Idea Futures&#8221- mechanisms. A similar concept underlies Long Bets and the Simon Exchange.

At Long Bets they say, “Long Bets is about taking personal responsibility for ideas and opinions.” That is the basic idea I had in mine when I suggested that “it would be a real public service to run well-conceived prediction markets based on the grandiose political pronouncements of the ‘chattering classes’.” It is all about an author taking personal responsibility for the opinions he publishes by, in effect via the prediction market, offering to fund countering opinions on well-defined claims if and only if those countering opinions turn out to be true.

(See also Chris Masse’s post. I’m not claiming any originality on my part here, I’m just trying to nudge the idea closer to common practice by suggesting a potentially interesting and fruitful area of application.)

Naomi Klein? Ann Coulter? Pat Buchanan? Michael Moore? Maybe they believe what they write, and would be willing to subsidize a prediction market out of their book royalties to demonstrate the strength of their convictions. Or how about the books from the current crop of U.S. presidential candidates—I wonder if these books contain any claims that are specific and substantive enough to be either true or false.

If such punditry-based prediction markets were common, mistaken-but-honest demagogues (those pundits who actually believe what they write, and are willing to stand behind it) would end up subsidizing more thoughtful analysts participating in the markets- correct honest demagogues would end up taking home larger financial rewards- and dishonest demagogues would dissemble, seek to avoid being pinned down on specific claims, and when pressed for actionable claims they would run and hide.

[Cross posted at Knowledge Problem.]

Small comforts of prediction markets

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Yesterday I had dinner with a friend I hadn&#8217-t seen for a few years. I asked what he&#8217-d been doing, apart from being a nerd, and he said he&#8217-d been spending too much time following the U.S. presidential campaigns (actually just the Ron Paul campaign, but that&#8217-s not particularly relevant here). I realized that I don&#8217-t do this anymore. It could be because I&#8217-m maturing, but I&#8217-ll give credit to prediction markets.

Most of the yapping in the media is about the horse race and personalities, which I don&#8217-t care about, other than the status of the former. Instead I check prices at Intrade most days, which gives me a more accurate and much more concise status update than any amount of time spent reading or watching commentary.

Furthermore, betting that candidates I detest will win and against candidates I mind less, even in small amounts, really helps me not waste time thinking (mostly distressed thoughts) about the election.

So thank you prediction markets for the time and peace of mind!

James Surowieckis The Wisdom Of Crowds… still stands.

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James Surowiecki&#8217-s 4 comments at Overcoming Bias (in October 2007), responding to accusations that he got it all wrong about Francis Galton:

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James Surowiecki&#8217-s 1st comment:

&#8220-Galton did not even bother to calculate a mean, as he saw his data was clearly not normally distributed. He used the median (of 1207), which was much further off than the mean, but by modern standards clearly the better estimator. It was Karl Pearson in 1924 who calculated the mean.&#8221-

Robin [Hanson], before repeating falsehoods, you might want to go back to the original sources &#8212- or, in this case, to the footnotes to my book. Galton did, in fact, calculate the mean, long before Karl Pearson did. Galton&#8217-s calculation appeared in Nature, Vol. 35, No. 1952 (3/28/07), in a response to letters regarding his original article. One of the correspondents had gone ahead and calculated a mean from the data that Galton had provided in his original piece, and had come up with the number 1196. Galton writes, &#8220-he makes it [the mean] 1196 lb. . . . whereas it should have been 1197 lb.&#8221-

I find the fact that Levy and Peart wrote an entire article about Galton (and, to a lesser extent, about my use of him), and never went back and checked the original sources is astounding in its own right. (They actually wonder in the paper, &#8220-However the new estimate of location came to be part of Surowieki’s account,&#8221- as if the answer isn&#8217-t listed right there in the footnotes.) What makes it even more astounding, though, is that they&#8217-ve written an entire paper about the diffusion of errors by experts who &#8220-pass along false information (wittingly or unwittingly)&#8221- while passing along false information themselves.

It also seems bizarre that Levy and Peart caution, &#8220-The expectation of being careful seems to substitute for actually being careful,&#8221- and yet they were somehow unable to figure out how to spell &#8220-Surowiecki&#8221- correctly. The article is a parody of itself.

I&#8217-m happy to enter into a discussion of whether the median or the mean should be used in aggregating the wisdom of crowds. But whether Galton himself thought the mean or the median was better was and is irrelevant to the argument of my book. I was interested in the story of the ox-weighing competition because it captures, in a single example, just how powerful group judgments can be. Galton did calculate the mean. It was 1197 lbs., and it was 1 lb. away from the actual weight of the ox. The only &#8220-falsehood&#8221- being perpetrated here are the ones Levy and Peart are putting out there, and the ones that you uncritically reprinted.

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James Surowiecki&#8217-s 2nd comment:

Here are the links for the letter from Galton, where he reports the mean:

http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_1.htm
http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_2.htm

There&#8217-s no reason for debate here. Levy and Peart say &#8220-Pearson’s retelling of the ox judging tale apparently served as a starting point for the 2004 popular account of the modern economics of information aggregation, James Surowieki’s Wisdom of Crowds.&#8221- It wasn&#8217-t the starting point. The starting point was Galton&#8217-s own experiment, and his own reporting of the mean in &#8220-The Ballot Box.&#8221- Robin writes: &#8220-Galton did not even bother to calculate a mean.&#8221- He did calculate it, and he did report it. This fact shouldn&#8217-t be listed as an &#8220-addendum&#8221- to the original post. The original post should be rewritten completely &#8212- perhaps along the lines of &#8220-Surowiecki and Galton disagree about which estimate is a better representation of group judgment&#8221- rather than &#8220-Author Misreads Expert&#8221- &#8212- or else scrapped.

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James Surowiecki&#8217-s 3rd comment:

I appreciate Levy and Peart admitting their mistake. But they seem not to recognize that their mistake undermines the critique that&#8217-s at the center of their paper. Their paper, they write, is about the misconstruing of Galton&#8217-s experiment. &#8220-A key question,&#8221- they write, &#8220-is whether the tale was changed deliberately (falsified) or whether, not knowing the truth, the retold (and different) tale was passed on unwittingly.&#8221- But the account of Galton&#8217-s experiment was not changed deliberately and was not falsified. It was recounted accurately. Levy and Peart want to use my retelling of the Galton story as evidence of how &#8220-experts pass along false information (wittingly or unwittingly) [and] become part of a process by which errors are diffused.&#8221- But there&#8217-s no false information here, and no diffusion of errors, which rather demolishes their thesis. If they really want to write a paper about how &#8220-experts&#8221- pass along false information, they&#8217-d be better off using themselves as Exhibit A, and tell the story of how they managed to publish such incredibly shoddy work and have prominent economists uncritically link to it.

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James Surowiecki&#8217-s 4th comment:

To finish, Levy and Peart insist that their really important point still stands, which is that &#8220-When people quote Galton through Surowiecki, they tell Surowiecki&#8217-s tale, not Galton&#8217-s,&#8221- and that this is a problem because Galton&#8217-s thinking is being misrepresented. But as I said earlier, &#8220-The Wisdom of Crowds&#8221- was not intended to be a discussion of Francis Galton&#8217-s opinions on what&#8217-s the best method to capture group judgment, nor, as far as I know, has anyone who&#8217-s &#8220-Surowiecki&#8217-s tale&#8221- used the Galton example since used it to analyze Galton&#8217-s opinions. People aren&#8217-t quoting the Galton story because they&#8217-re interested in what Galton himself thought about the median vs. mean. They&#8217-re quoting it because they&#8217-re interested in the bigger idea, which is that group judgments (and this is true whether you use the median, the mean, or a method like parimutuel markets) are often exceptionally accurate. Levy and Peart have constructed a straw man &#8212- and, in this case, a straw man based on a falsehood &#8212- and then tried to knock it down.

Robin [Hanson] writes: &#8220-it is ironic that Galton made quite an effort to emphasize and prefer the median, in part because the data did not look like a bell curve, while your retelling focuses on him calculating a mean after checking for a bell curve.&#8221- What&#8217-s ironic about this? He did check for a bell curve, and he did calculate the mean. It&#8217-s the data themselves, not Galton&#8217-s interpretation of them, that I was writing about. (If he hadn&#8217-t calculated the mean, I would have happily told the story with the median, since it was also remarkably accurate, and demonstrated the same point about the wisdom of crowds.)

Finally, on the substantive question, Robin (and Levy and Peart) seem to think that because the distribution of guesses wasn&#8217-t normal, that makes using the mean a mistake. But this is precisely what&#8217-s so interesting: if the group is large enough, even if the distribution isn&#8217-t normal, the mean of a group&#8217-s guesses is nonetheless often exceptionally good.

Prediction Markets = Clear Expiry + Disperse Information + Participation Incentives

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Jed Christiansen at Forbes (just after John Delaney&#8217-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&#8217-t as good as they (or anyone else) think they are. It&#8217-s simply better to ask the crowd in these cases.

Missing from Jed Christiansen&#8217-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&#8230-

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&#8217-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.

How to sell art short

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No GravatarFor a while it seemed like a month wouldn&#8217-t pass without hearing of a new record-breaking art auction, along with the inevitable insinuations of a &#8220-bubble&#8221-. 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 &#8217-80s / early &#8217-90s 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:

  • 2009 tax futures yielding 1.5%
  • Intrade, with carry
  • Talking tax futures on BNN, Canada’s business channel
  • Tax Futures, “In Real Life”
  • YooNew, fears and hopes

If Musharraf goes, should we celebrate?

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Benazir Bhutto made a compelling case in the Sunday New York Times that she would be a better partner for the West than Musharraf. As she noted, $10 billion in U.S. aid since 2001 has not resulted in the elimination of Al Qaeda&#8217-s base there. There seems to be substantial reason to believe that Pakistan and its intelligence service are part of the problem, not the solution.

But would Musharraf&#8217-s fall be good news? It&#8217-s not obvious, since we don&#8217-t know who will replace him (i.e., Bhutto or someone more anti-Western). And even if it&#8217-s Bhutto, we don&#8217-t know how much help she&#8217-ll be once in office.

Intrade has just listed a contract that may help provide an answer. In addition to adding Musharraf to their foreign leader departure series (as Chris noted yesterday), they also added a parlay for Musharraf leaving and Osama being captured (at my suggestion). So if these contracts turn out to be liquid, we&#8217-ll be able to get a market-based estimate of the correlation between Musharraf and a reasonable summary statistic for whether outcomes in Pakistan are good for the West.

Of course, the usual caution about correlation and causality applies here. If Osama is caught tomorrow, it probably helps Musharraf keep his job. The longer term conditional probabilities should be less contaminated by this problem and the difference betweens between the prices of the long and short dated contracts might be used to contract a clean(er) estimate of a causal effect.

This seems like the most interesting geopolitical decision market to come along in a little while. But it&#8217-ll only work if it&#8217-s liquid. So those of you with Intrade accounts, put up an order or two. Your country needs you.

Price for Pakistani National General Election Date at intrade.com

Price for Pervez Musharraf (Pakistan) (Rule 1.8 Applies) at intrade.com

Price for Osama Bin Laden at intrade.com