Category Archives: Prediction Markets

Refuge Markets

The topic of global catastrophic risk seems silly to many, and my conference talk last Friday on refuges against human extinction seemed even sillier to some – Ron Bailey had fun comparing me to Dr. Stranglelove, and Spiegel saw a colorful character.  Silly or not, however, refuges seem a cheap way to save humanity from worst-case disasters.

My talk went beyond my book chapter to reach a new height of silliness – I suggested refuge ticket markets.  Beyond my obvious need to be sillier-than-thou, I had another motive: to let prediction markets identify scenarios where catastrophe is a serious risk, and then advise us on how to avoid these scenarios.

You see, speculative markets have an obvious problem forecasting the end of the world, as no one is left afterward to collect on bets.  So to let speculators advise us about world’s end, we need them to trade an asset available now that remains valuable as close as possible to the end.  Refuge tickets fit that bill.

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Cloud Seeding Markets

Nature considers cloud-seeding:

Chinese meteorologists will use weather-modification technologies to try to stop rain from spoiling the [Olympic] party. … Official figures … say that the country created 250 billion tonnes of rain between 1999 and 2006. … Critics say that many of these claims are laughable, and that most of the projects under way are based on little more than faith. … Today, countries from Australia to Iran practise some form of cloud-seeding – as do nearly a dozen US states. …

Some Chinese rain-makers have tried to conduct controlled seeding experiments. … In the early 1990s, the researchers found that rainfall rose by 18% as a result of 21 seeding operations – but the sample was too small for the results to be statistically significant.  In an earlier study, conducted between 1975 and 1986, meteorologists in … southeast China, conducted a randomized seeding experiment with two 14,000-square-kilometre regions. Over the course of 244 experimental days, they found that areas that had been seeded had 20% more rainfall than did those that had been left to their own devices.

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CFTC Event Market Comment

In May the US CFTC declared that it was considering offering more legal approval for "markets commonly referred to as event, prediction, or information markets."  They requested comments, due by today.  My comment concludes:

In addition to existing regulatory regimes for ownership-hedging securities, idiosyncratic-risk-hedging insurance, and common-risk-hedging futures, it could make sense to have a distinct regulatory regime for markets whose main reason to exist is the info that they collect.  Compared with existing commodities futures regulation, such a regime should set a much lower barrier to creating such markets, as much of the social value may be distributed in millions of small markets.  And while it is hard to determine in general which markets would create high social info value, relative to cost, we should presume such high value when a sponsor is willing to pay to ensure that traders suffer no average financial cost from their participation.

Added:  I’m off in a few hours for a two week trip to Helsinki and then Oxford.  I have posts ready for while I’m gone, but I expect to comment less often. 

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Prediction Market Based Electoral Map Forecast

Slashdot points to ElectoralMap.net, a site which aggregates the Intrade prediction market results for individual states in the fall U.S. Presidential election, to predict aggregate electoral college totals and the election winner. I’m bookmarking it as an alternative to media coverage of the race, which will put their own spin on likely outcomes. Note the arrows at the bottom of the map will allow you to track the changes in sentiment over the weeks and months leading up to the election.

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Prediction Markets and Insider Trading

The NYT reports:

With Internet gambling predicted to surpass $20 billion in 2008, and with illegal wagering accounting for $150 billion in the United States, by some estimates, the temptation for those seeking to influence the outcome of games has never been greater. Now, a raft of gambling scandals in sports, from cricket to soccer and most recently tennis, has raised an uncomfortable question: Are the games we watch fixed?

Part of the reason why sports is more vulnerable to manipulation is that, as I have long argued, they don’t matter:

Who wins these sporting contests is irrelevant. It does not matter, except inasmuch as people choose to make it matter. It does not make the world a better or worse place…Much of the lure of sports lies in the illusion that they are important. It is pretty clear, when you think about it, that they aren’t, but the illusion is strong. After all, an awful lot of people care about them. Our newspapers in the morning and news shows at night have a business segment, a political segment, and a sports segment, implying that these sectors are of equal value. There are magazines devoted to sports…It is no wonder that so many are fooled into taking them with far more seriousness than they deserve.

A CEO who manipulates his firms profits is manipulating something deeply attached to the real world: a measurement of how much value his firm is producing.  Since this value is hard to measure, there are ways to jigger the accounting, but they are inherently temporary.  Accumulated profits should appear in physical form, like cash or securities, or valuable property.  Eventually, Ponzi schemes and companies like Enron get caught, because their accumulated physical assets don’t match their claimed profits.

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Idea Futures In Lumpaland

Continuing the parable

Dragon markets were an exciting new fad in Lumpaland – any Oopma could bet valued cocoa beans on dragon locations, lifespans, and victim counts, and on how these might change with anti-dragon policies.  At first, instituters and amateurs both tended to dismiss markets that disagreed with favored estimates.  But as dragon markets accumulated an impressive track record, Oopmas slowly became more reluctant to disagree.  Dragon policy became better informed, more dragons were dispatched, and eventually some funds were even diverted from the institute to subsidize dragon markets. 

Yet while some instituters and amateurs came to specialize in dragon market trading, most continued with previous activities.  Most amateurs found it too tedious to specialize on particular dragons to the degree required to win bets – witty widely-read amateurs were invited to more parties.  And most instituters found that winning in the markets just did not impress to the same degree – most audiences preferred eloquence, gadgets, and math as signals of personal impressiveness. 

Prediction markets have great potential to improve info in science and business, but they’ll only go as far as demand for such info.  To the extent we really care more about affiliating with impressive folks, we’ll prefer activities and institutions that better achieve this end. 

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Lobbying for Prediction Markets

Today I first appear in Science as an author (last time I was news), though I have eighteen coauthors.  It is a Prediction Markets "Policy Forum" (ungated here): 

Prediction market prices can be used to increase the accuracy of poll-based forecasts of election outcomes, official corporate experts’ forecasts of printer sales, and statistical weather forecasts used by the National Weather Service.

Several researchers emphasize the potential of prediction markets to improve decisions. The range of applications is virtually limitless – from helping businesses make better investment decisions to helping governments make better fiscal and monetary policy decisions.

Prediction markets have been used by decision-makers in the U.S. Department of Defense, the health care industry, and multibillion-dollar corporations such as Eli Lilly, General Electric, Google, France Telecom, Hewlett-Packard, IBM, Intel, Microsoft, Siemens, and Yahoo. The prices in these markets reflect employees’ expectations about the likelihood of a homeland security threat, the nationwide extent of a flu outbreak, the success of a new drug treatment, the sales revenue from an existing product, the timing of a new product launch, and the quality of a recently introduced software program.

These markets could assist private firms and public institutions in managing economic risks, such as declines in consumer demand, and social risks, such as flu outbreaks and environmental disasters, more efficiently.

Unfortunately, however, current federal and state laws limiting gambling create significant barriers to the establishment of vibrant, liquid prediction markets in the United States. We believe that regulators should lower these barriers by creating a legal safe harbor for specified types of small stakes markets, stimulating innovation in both their design and their use.

Coincidentally, on May 1 the CFTC asked for public commentary on regulating prediction markets – comments due July 7.

Should-not-be-needed disclaimer:  Such an endorsement says only that I estimate this change to improve on the status quo. 

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If I Had A Million

I’ve been telling folks for a long time that if I had a million dollars to spend on a project, I’d implement an idea I posted first twelve years ago today, and described in Forbes sixteen months ago:

Make two subsidized real-money markets on the stock price of each Fortune 500 firm, one market conditional on its CEO stepping down by quarter’s end, and the other conditional on not stepping down.  The difference between these two prices would advice the board on dumping the CEO.

If active, these markets should attract business press, and then most of these CEOs would come to see what the markets say about them.  Half a million would pay for legal/admin.  The other half would only cover a $1000 subsidy per firm, but CEOs trying to manipulate would add lots of liquidity.  A few years of data would let us clearly compare the returns of firms following market advice to firms not following.   With clear data I’d encourage shareholders to sue boards ignoring market advice, and after a few wins most boards would weigh market advice heavily.   A revolution in CEO accountability would then be complete, all for only a million.

Technically, I’d also create a third market per firm in the chance the CEO will step down, and force the three prices to be consistent with external stock prices, so there’d only be two independent degrees of freedom.

Added: And of course this would be a huge foot-in-door legitimization and exposure for many other kinds of organizational decision markets.

Added July 2020: I reaffirm that this is the project I’d fund with a million.

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Cash Increases Accuracy

From the current New Scientist:

In an experiment dubbed "Cola Wars", [Nick Epley] conducted a taste test with a twist: he told participants which cola was Coke and which was Pepsi before tasting began. After tasting, all they had to do was estimate what percentage of their friends would be able to distinguish between the two in a blind taste test. Studies show that people’s ability to do this is no better than chance – so an answer around 50 per cent would be right. What Epley found was intriguing. When he motivated volunteers to give a considered response – by offering them a cash payment – their answers tended to be close to 50 per cent. Subjects who were not paid, however, seemed to answer with an egocentric bias: since they knew which cola was which, they assumed that a high proportion of their friends would guess correctly (Journal of Personality and Social Psychology, vol 87, p 327).  For Epley, the finding supports his idea that putting yourself inside the head of another person and considering their perspective requires a cognitive effort that simple egocentric judgements do not.

Make no mistake: stronger incentives often (though not always) make us see more clearly.

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Colorful Character Again

I just learned of a new Scientific American article on prediction markets, which is pretty positive: 

A paper … compares the performance of the IEM as a predictor of presidential elections from 1988 to 2004 with 964 polls over that same period and shows that the market was closer to the outcome of an election 74 percent of the time. … Attracted by the markets’ apparent soothsaying powers, companies such as Hewlett-Packard (HP), Google and Microsoft have established internal markets that allow employees to trade on the prospect of meeting a quarterly sales goal or a deadline for release of a new software product. As in other types of prediction markets, traders frequently seem to do better than the internal forecasts do. … Prediction markets may truly hark back to the future. "My long-run prediction is that newspapers in 2020 will look like newspapers in 1920," Wharton School’s Wolfers says. If that happens, the wisdom of crowds will have arrived at a juncture that truly rivals the musings of the most seasoned pundits.

But I am personally singled out as the colorful character who is way too positive: 

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