Monthly Archives: November 2006

Avian Flu vs Dow Jones

The Global Risks prediction market that we built for the World Economic Forum (aka Davos) received some attention in the Financial Times online yesterday. Here’s a link to the story.

Global Risks PMThe article mentions the brand new markets we set up for Thomson Financial, which is a partner of the WEF’s Global Risks program. These markets, designed to forecast the impact that a hypothetical Avian Flu pandemic might have on the Dow Jones Industrial Average, are worth mentioning for several reasons:

First of all, they are true conditional markets, meaning that their purpose is not to forecast the future, but to forecast several alternative futures. In this case, it means forecasting the impact on the Dow of increasingly severe pandemic scenarios: from les than 20 countries with confirmed human cases of the disease, to more than 75.

Secondly, these are not markets in the conventional sense. Rather, we are using our innovative Competitive Forecasting design, where participants repeatedly enter and review their forecasts as high-low pairs of values and get scored, in the end, on how accurate and precise their forecasts turned out to be. This is easier to use than even the friendliest trading markets, primarily because it doesn’t artificially force participants to translate their forecasts into buy/sell decisions. They can just enter their forecasts directly with no extra mental gymnastics. It also yields richer prediction data than a mere sequence of prices and trading volumes. We’ve been implementing such Competitive Forecasting “markets” inside corporations for more than a year with great success (more about that later), but the Thomson/WEF implementation is a rare public showcase of this proprietory technology.

Finally, the Thomson/WEF markets are breaking some new ground: they may well be the first pure information markets – their only purpose is to generate information unavailable by other means – whose output is being carefully tracked by a major Wall Street “player”. When the hard core financial types start paying attention to play-money prediction markets, as in this case, it bodes well for wider acceptance of the technology.

Here are a couple of quotes from the Thomson Financial press release of November 27:

Jesse Fahnestock, Global Leadership Fellow, The World Economic Forum commented: “Most global risks are difficult or impossible to assess quantitatively, but in today’s competitive and interconnected business environment, understanding these risks is increasingly important. Predictive markets aggregate collective wisdom, helping to overcome perceptual and cognitive biases, and could be an excellent tool for investors and other decision makers struggling to understand the potential impact of risks such as avian influenza.”

Thomas Aubrey, Investment Management Director, Thomson Financial added: “The key to successful risk management is to focus on those risks that truly matter and ensure that the impact of these risks is understood and mitigated. Thomson Financial’s risk indicators help provide corporate executives with a balanced approach to understanding the new risk paradigm — highlighting those risks, be they financial or non-financial, which are really relevant”.


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Political predictions: Does money matter?

Play-money prediction markets can be just as accurate, if not more accurate, than their real-money counterparts. As far back as 2003, NewsFutures helped prove this point by running a large scale real-world experiment comparing its play-money NFL football predictions with those of Tradesports. Esteemed scholars David Pennock (Yahoo!) and Justin Wolfers (Wharton) analyzed the data and concluded that both sets of predictions were just as accurate (and both were more accurate than the vast majority of individual “experts”). The resulting peer-reviewed article (here in pdf format) caused quite a stir because of the deeply ingrained real-money bias harbored by most economists.

It is worth revisiting this issue once more in the light of the recent U.S. mid-term elections. Tradesports and NewsFutures were again running comparable prediction markets on the subject. In the comparative chart below, it appears that NewsFutures play-money traders called the Democratic-House outcome earlier and more decisively than Tradesports’ real-money traders. (This snapshot was taken on the morning of Nov 6, on the eve of election day.)


Based on this single observation , we wouldn’t want to claim that NewsFutures’ political predictions are better that Tradesports, but we certainly would conclude that if you’re looking for some serious political predictions, you just cannot dismiss play-money markets out of hand.

NewsFutures operates both play-money and real-money markets (where legal, of course), and we are very aware of the different sets of challenges and rewards that are inherent in each type of implementation. But we’ve also learned that if you’re just looking for accuracy, everything else being equal, money just doesn’t matter.

For companies who want to internalize a prediction market but are not allowed to use a real-money implementation, this is very good news!

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