I’ve known John for some time; though we only met for the first time in October 2007.  I was struck by how down-to-earth he was, and truly interested in having everyone in the prediction market industry succeed.  At the time, Intrade was going through a legal separation of sorts from its other entity Tradesports, and many had questions and concerns about what that meant.  John was incredibly honest and up-front, and didn’t pull any punches in speaking about the issues.

To make this tragedy even worse, his wife gave birth to a baby daughter just before he made his way to the summit.  He died without knowing he had become a father once again.

I will personally remember John as a successful entrepreneur and as a man who embodied the friendly and big-hearted nature of the Irish.  He will be truly missed.

Rest in Peace, John.

Other Obituaries/News

New York Times

Daily Mail

Justin Wolfers (Freakonomics blog)

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Early this year I posted my predictions for 2009. In the best spirit of Robin Hanson (getting better predictions by simply tracking how close predictions matched reality), I want to see how I did.

• “Prediction markets in 2009 are going to become even more well-known and wide-spread, but there will be no single event that brings them to the attention of the public. It’s going to be a slow, but steady, growth.” – This was spot on. All of the vendors appear to be doing well, but there was no big “event” that brought everyone attention.
• “All of the prediction market vendors will mature their business offering/proposition.” – Not having been on the receiving end of any of their sales pitches, I can’t say this one is true for sure. But from their blog posts and public statements I would assess this as likely.
• “HubDub will continue to only be the only strongly popular play-money prediction market.” – Put me down as wrong on this one. Nigel and the creators of HubDub have focused their time and effort on FanDuel instead. (Rightly, for revenue reasons!) So while HubDub is still active, it’s not the hive of activity it was for a while.

That said, I’m still a fan of niche, public, popular sites like HSX. They managed to turn play-money prediction markets into a real-money revenue stream by analyzing trader behaviour (which can only be seen by administrators) and selling that business intelligence to the studios. This could be replicated in many industries, such as video games or television.

• “While a couple additional software vendors may appear, I get the feeling that the market for prediction market software is largely saturated.” – This was also spot on.
• “I’m looking forward to see how the CantorExchange develops.” – Not so much a prediction, but a hope that it proved interesting. It’s taken a long time to get up and running apparently, and won’t be widely launched for real-money contracts until 2010. (If I read the website correctly.)

A great development from InTrade

Just yesterday John Delaney of InTrade posted on his blog that InTrade will soon be offering some historical market data to the public for free. (As he notes, this means they’re losing a source of potential revenue, as historical data can be quite valuable.) This is a great development, and should be a solid source of data for people to dig in and get interested in how traders operate in a prediction market. Kudos to John for doing this.

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#1 – Trading UK Housing Prices

CityOdds, based in London, has recently opened a prediction market (currently marketed as a competition) to predict a UK housing market index. While this is a play-money market, there is a £10,000 first-place prize.

CityOdds runs both fantasy markets, as well as real-money markets on currencies and other commodities. Mike Chadney, the founder, is a good guy and experienced “City” man. Check out the housing market here: http://www.cityodds.com/hpitrading.html

#2 – Predictify shuts down

Predictify made a bit of a splash when Scott Adams used them to forecast how many sales of his (then) new book were going to be sold.

It seemed a bit of an odd company; venture-funded, but with people who had no background in prediction markets at all. They offered a small number of markets where accurate forecasting would win cash, while most markets were just for leaderboard position. (My trading was perhaps typical: I’d log it and only scan the markets where I could win cash and ignore the rest.)

Well, they’ve died. According to an announcement on their website:

Due to the tough economic climate, we are planning to cease operations and shut down the company in the near future. If you have an account balance of $20 or more, please visit your account page and enter your withdrawal information by 11:59pm on August 31, 2009 to receive payment.

We sincerely enjoyed building and operating Predictify, and we’re glad that you could be a part of it.

The Predictify Team

My question is this: what does this mean for Crowdcast?

Crowdcast has an absolutely fantastic team who have great experience in prediction markets. But can they thrive as a venture-funded company? I’m hopeful, but perhaps am more skeptical that there are simply enough customers truly interested in their level of solution. Particularly as so many companies need hand-holding and thus a lot of expensive people-time through the early stages of implementation, are the profits sufficient to satisfy investors?

I don’t know, but I do believe they’ve at least got the people to give it a go. (Strangely enough, it was Crowdcast’s founder Mat Fogarty who originally told me about Predictify well before their launched.)

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Economist article

A recent article on prediction markets in the Economist was titled “An uncertain future.” I would describe its attitude toward prediction markets as mixed. Here are a few selected quotes:

“But although they have spread beyond early-adopting companies in the technology industry, they have still not become mainstream management tools. Even fervent advocates admit much remains to be done to convince sceptical managers of their value.”

“Koch says the results so far have been pretty accurate compared to actual outcomes, but stresses that markets are complementary to other forecasting techniques, not a substitute for them.”

“Another reason prediction markets flop is that employees cannot see how the results are used, so they lose interest. [...] its most effective trials took place in areas where managers could do something with their findings, making staff feel that trading was worthwhile.”

“Bosses may also be wary of relying on the judgments of non-experts. Yet many pilot projects run so far have shown that junior staff can often be surprisingly good forecasters.”

So I believe the article is generally positive toward the possibility of prediction markets, but generally negative toward the lack of adoption. Which is fair; though I think some good success stories have been kept quiet by some companies for competitive advantage and corporate ego.

Chris Masse’s reaction

Chris Masse has been writing about the prediction market industry for a number of years, and started his blog MidasOracle in about 2006. Strangely, Chris’ writings on prediction markets have become quite negative in recent months. As I understand it, he’s become quite irritated that prediction markets have been touted as “vastly superior” to polls in elections, and other general marketing in the industry. The front page of MidasOracle now has the following statement (his emphasis removed):

The Truth about Prediction Markets

The social utility of the prediction markets is marginal. Number one, the aggregated information has value only for the totally uninformed people (a group that comprises those who overly obsess with prediction markets and have a narrow cultural universe). Number two, the added accuracy (if any) is minute, and, anyway, doesn’t fill up the gap between expectations and omniscience (which is how people judge forecasters). In our view, the social utility of the prediction markets lays in efficiency, not in accuracy. In complicated situations, the prediction markets integrate expectations (informed by facts and expertise) much faster than the mass media do. Their accuracy/efficiency is their uniqueness. It is their velocity that we should put to work.

Remember, dear readers, you heard it here first —on Midas Oracle.

Part of my issue is his definition of “social utility”: namely that I’m not exactly sure what he’s talking about. I completely understand the concept of utility, but “social utility” is a phrase that could mean a variety of things, and I don’t know exactly what Chris means when he writes about it.

My other response to Chris is that I feel he doesn’t distinguish between public and internal prediction markets when he discusses marketing and usage of these markets. I’d like to discuss these issues here.

Public prediction markets

Public prediction markets are tricky things. They’re tricky to get a critical mass of people involved, they’re tricky to get a flow of interesting and valuable contracts, and they’re tricky when events happen that don’t easily conform to how the contracts were established. That said, there are a handful of good and interesting public PM’s. InTrade and Betfair both offer real-money markets, and the better play-money markets include Hubdub, Inkling, Newsfutures, and HSX.

These markets do get press, particularly InTrade in the run-up to the last two presidential elections. InTrade in particular seems to be irritating Chris because of the data point that they forecasted all 50 states correctly. (Which as I’ve written before probably means that the markets weren’t running as efficiently as they could; you’re supposed to get market “failures”.) And I agree with him that too much has been made of this data point.

Overall, I think Chris rightly addresses the issue of the value of public prediction markets. In many cases they’re purely entertainment, and in other cases (even the elections), they’re not necessarily better predictors than other methods. That said, they do incorporate new information faster than any other forecasting model. But I believe Chris wrongly applies these same criticisms to a completely different model, internal prediction markets.

Internal (corporate) prediction markets

Internal prediction markets seek to do either of two things:

• forecast something important to the company where they already have a prediction
• forecast something that’s never been predicted before

When it comes to the first point, forecasting something that the company already forecasts, prediction markets may or may not be an excellent solution. I’ve seen one set of markets that absolutely blew away the accuracy of current forecasts, and I’ve seen other markets that were consistent with current forecasts with little or no accuracy edge. In this case, prediction markets can serve as a fairly low-cost “reality check” on the official forecasts. When they deviate too much, it will raise a flag for investigation. This deviation is particularly helpful since prediction market forecasts are real-time, and can react instantly to new news.

I think the second point above is perhaps the most valuable opportunity. Simple ideas like using a prediction market to establish a RAG status could potentially be very powerful in a company. Depending on the value of the information forecasted, even a moderately accurate prediction market could be incredibly useful to a company.

Chris also over-reacts to some of the marketing from software vendors. Yes, some may mention events like InTrade predicting all 50 states in 2004, but that’s just a party trick to get people interested and in the door. Companies first need to be convinced that the tool works, then they need to be convinced that it works for them. The second part is done individually with their clients so we don’t see it. (Though I really like the case studies that Inkling have put on their website.)

I personally think that he gives too much credit to the popular press in raising the profile of prediction markets; far more credit is due to James Surowiecki and “The Wisdom of Crowds.” (Amazon link)

Summary

Prediction markets are interesting tools, but the lessons learned from public prediction markets are different than those learned from internal prediction markets. It’s important that these two applications are not confused. There will always (and rightly) be questions about the accuracy of prediction markets. In some cases it’s clear that markets are superior, in some internal cases it doesn’t matter since nothing is forecasted right now, and in other cases markets will be about as accurate as what’s already predicted. But in all three cases there is still a valuable argument as to why prediction markets should be used. It all comes down to the specific needs of an industry or company, which is where the vendors step in to help.

The results speak for themselves. Each year there are more software vendors, and each year the existing software vendors hire more people to serve their clients. I’m not going to try and predict the long-term future, but I believe the short-term future is positive.

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What I expect for prediction markets in 2009

I’m probably going to regret doing this by the end of the year, but I’m going to put on my forecasting hat and try to predict what will happen this year in the field of prediction markets.

• Prediction markets in 2009 are going to become even more well-known and wide-spread, but there will be no single event that brings them to the attention of the public. It’s going to be a slow, but steady, growth.
• All of the prediction market vendors will mature their business offering/proposition. Both InklingMarkets and Xpree have made recent business development hires, and Inkling recently redesigned their website with a stronger business pitch and case studies. I think that business cases for prediction markets will be more clear and more developed in general because of this.
• HubDub will continue to only be the only strongly popular play-money prediction market. (HSX is probably similarly popular, but is a single-industry prediction market.) With Hubdub’s partner program and social networking features, they will see significant growth this year.
• While a couple additional software vendors may appear, I get the feeling that the market for prediction market software is largely saturated. People working on projects part-time and selling them may proliferate and be suitable for the lower end of the market, I don’t see many more serious prediction market software companies starting up in 2009.
• I’m looking forward to see how the CantorExchange develops. Will there be enough customers? Will the market see the effects of other studios trying to bid the prices of their competitors’ films down? Or will it be seen more as a financial hedging tool for institutions involved in the film industry? There are lots of open questions to evaluate here, but I still maintain it’s a great step forward for the prediction markets industry.

What to expect from this blog in 2009

I’m going to continue posting on both prediction markets, but continue talking more and more about how collective intelligence can be used in other contexts. Specifically, I’ve become really interested in how groups of people develop new ideas and new innovations.

As I’ve written before, I really don’t like the word “innovation.” Bruce Nussbaum at BusinessWeek has written a few things lately that I really like:

“Innovation” died in 2008, killed off by overuse, misuse, narrowness, incrementalism and failure to evolve. It was done in by CEOs, consultants, marketeers, advertisers and business journalists who degraded and devalued the idea by conflating it with change, technology, design, globalization, trendiness, and anything “new.” It was done it by an obsession with measurement, metrics and math and a demand for predictability in an unpredictable world.

and

“Innovation” is inadequate as a concept to deal with these changes. You have “game-changing” innovation, which is big but rare and incremental innovation which is small but common.

The truth about innovation is that it takes groups of people a lot of work to find and develop new ideas and turn them into innovations. Scott Berkun has a great chapter in his book “The Myths of Innovation” where he destroys the myth of the lone creative genius.

We know it takes groups of people to make innovation happen, so where are the tools for it? A lot of time, money and effort has gone into social networking software to connect people, such as Facebook, MySpace, etc. But I have to agree with Tim O’Reilly: we need to stop throwing sheep and do something worthy. But those tools can be very useful to us in helping foster innovation. I reviewed the software for idea and innovation software recently, but was left generally unimpressed.

These are some of my current thoughts. I plan on thinking out loud more in 2009 on these topics and seeing where it takes me. I look forward to your feedback.

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Are you a successful trader on the Hollywood Stock Exchange (aka HSX)?

Well, now you could potentially turn that expertise into cold, hard cash. Cantor Fitzgerald, the company that owns HSX, has announced a real-money equivalent, the Cantor Exchange. On it you’ll be able to trade “Movie Box Office Contracts.”

It was officially announced Monday, December 8th through press releases on the new CantorExchange website. To quote from the press releases:

Cantor Fitzgerald, L.P., a leading global financial services firm, announced today that it has filed an application with the Commodity Futures Trading Commission (“CFTC”) to launch the Cantor Exchange. Cantor Exchange intends to list Domestic Box Office Receipt contracts as the exchange’s first traded product.

[...]

Subject to final regulatory approval of the Cantor Exchange application, Domestic Box Office Receipt contracts will offer film finance professionals and traders a new opportunity to hedge and speculate on the theatrical performance (ticket sales) of major film titles. Domestic Box Office Receipt contracts will be a next generation financial management tool that allows film professionals to hedge risk and provides speculative opportunities to other market participants based on the first four weeks of a film’s box office performance.

The first Domestic Box Office Receipt contract is expected to be listed on the Cantor Exchange in the first quarter of 2009, subject to final approval of the Cantor Exchange application by the CFTC.

If you’re willing to sit through the video’s cheesy music on the site, you’ll find out that traders can get started with $50 in their account. It appears they’re pitching the buy-side (generally) for fans looking to share in the up-side and pitching the sell-side (generally) for investors and others looking to hedge their investment.

Each contract starts with a week-long auction to determine the starting price. Every 24 hours the exchange will publish the overall market price that would be achieved based on all the buy and sell orders entered. Before going to continuous trading, all buy/sell orders will be cleared at the single best market price.

Summary

I think this is great news, as it starts to push the boundaries of acceptance of futures (aka “prediction”) markets. I wish Alex and the rest of the team there all the best luck in the approval process and look forward to trading a bit there myself!

It should be interesting to hear what the mainstream press thinks of this development.

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Probabilistic predictions (and prediction markets)

The most popular prediction markets this election season were probabilistic markets, where the payoff was either 1 or 0. (In the case of InTrade, $10 or $0.) The market price can and is interpreted as a percent probability that the contract will take place; one of the candidates getting elected. Unfortunately, many commentators believe that once a contract is above 50% that the candidate will win, and if a candidate is above 50% in a given market and doesn’t win, the prediction market has failed.

This is completely wrong.

I’ve discussed in previous posts that you have to be wrong in order to be right. As a quick reminder:

• 98% chance = 1 in 50 will be wrong
• 90% chance = 1 in 10 will be wrong
• 80% chance = 1 in 5 will be wrong
• 75% chance = 1 in 4 will be wrong
• 67% chance = 1 in 3 will be wrong
• 50% chance = 1 in 2 will be wrong

So how did the prediction markets do? And how did fivethirtyeight.com do in comparison? (They’re the only site I know of that takes poll results and turns them into probabilistic forecasts mathematically.) Here’s a quick snapshot:

InTrade results

We immediately run into the primary problem with evaluating these markets… while there are 50+ markets, only a small number of these were not at the extremes of the scales. I’ve just included those with a market price of <90%.

This looks great for InTrade, but it's deceiving. For example, let's take a look at all contracts at approximately 80%. (FL, OH, VA, NV, and CO). They have an average market price of 82.6%. If InTrade was perfectly calibrated, one of these should have been wrong.

It looks better on the other side. If you calculate MT, GA, ND, and IN they have an average market price of 26.75%. In fact, one of these four were wrong (Indiana).

For the mathematical amongst you, it should be clear that this type of assessment is quite crude. When you have so few data points, you need to pick and choose "bins" of data with your own best judgement. Ideally there would be enough markets that you could create strict "bins" of data and measure against those. (This is exactly how Inkling created their plots here… I would encourage you to read their post, too.) Unfortunately, we only have a small number of “battleground” markets and this just isn’t possible.

Fivethirtyeight.com results

In my opinion, fivethirtyeight.com appears to have done marginally better. Take the bottom five markets shown, which have a combined probability of 15%. In fact, one of these five actually occurred; a 20% success rate.

Another slice of data shows the same thing: MT, ND, IN, and MO have an average probability of 30% and an actual success rate of 25%. Taking MO, NC and FL the probability was 61%, and and actual success rate of 67%.

I say that fivethirtyeight.com has done marginally better because I could take reasonable slices of data throughout their predictions and come up with reasonably calibrated results. I had to specifically pick and choose to find similar results with InTrade. In other words, the fivethirtyeight.com forecasts were more internally consistent.

Non-probability predictions (and prediction markets)

Some of the lesser-cited and more lightly-traded prediction markets for the 2008 election cycle were on index markets on the vote share for each candidate. Here was the final tally of the national vote:

• Democrat – Obama – 52.7%
• Republican – McCain – 46.0%
• Other – 1.3%

What did the Iowa Electronic Market forecast? (Data from midnight on the 3rd)

• Democrat – Obama – 53.5% (0.8% error)
• Republican – McCain – 46.4% (0.4% error)

What did fivethirtyeight.com forecast?

• Democrat – Obama – 52.3% (0.4% error)
• Republican – McCain – 46.2% (0.2% error)
• Other – 1.5% (0.2% error)

To be fair, fivethirtyeight.com was the best of the “poll aggregators”. Real Clear Politics and Pollster.com came up with the following:

• Democrat – Obama – 52.1%, 52.0%
• Republican – McCain – 44.5%, 44.4%

It’s clear from this data that while the Iowa Electronic Markets were quite accurate, fivethirtyeight.com forecasts were even more accurate.

For reference, redbluerichpoor.com showed the following result from fivethirtyeight.com’s final forecasts (of state vote share) which were pretty accurate:

The issue of time

Recently, George Neumann of the Iowa Electronic Markets sent out a document to the Prediction Markets Google group that claimed that the IEM “continue to dominate polls.” One specific line really struck me as ridiculous:

During this 886 day period the average absolute error was 1.2%, amazingly similar to the final polling results but for a much longer period.

So now we’re supposed to assess the accuracy of a prediction market over a 2+ year period?!? So as the race moves and swings, and the markets with it, the IEM seems only to be concerned about the average. This implies that the election is much more static than I believe it to be.

Face it, the race changes. If the election was held within a week of the Republican convention, John McCain would have likely won… the markets reflected that. But events change, and the market changes along with them. This is why I disagree with Peter McClusky’s analysis of price changes here.

Uncertainty is priced into prediction market prices; in the fall Nate Silver of fivethirtyeight.com was consistently predicting a much higher probability of Obama winning the race than prediction markets, because the uncertainty of events between the forecast date and the election was priced into the market. As the election date got closer the uncertainty was removed from the price and Obama’s price went up. But this happens rather late in election futures; in election after election we’ve seen examples of late-breaking news that has had the ability to shift the outcome of a race.

Where does this leave prediction markets?

Were prediction markets consistently better than a well-performing site like fivethirtyeight.com? No.

Were prediction markets consistently worse than a site like fivethirtyeight.com? No.

They perform largely the same, though the final accuracy of fivethirtyeight.com was a tad bit better than InTrade/IEM. But the purpose of the two types of sites are different.

Fivethirtyeight.com and similar sites take current data and process it to extrapolate trends. These sites lag real events; Nate Silver mentioned on a number of times that he expected his model’s forecast to move, but that it hadn’t because the relevant polls hadn’t hit the model yet. Between the time a poll closes, the result released and then incorporated into the model is anything from a day or two to several days. So while it looks quite accurate, a poll aggregator is a lagging indicator. (Another couple of election cycles will tell us if their accuracy continues or was just a fluke in 2008.)

Prediction markets show the results of what a group of traders believe what will happen. This includes polling data, but also reacts to real-time information. A candidate makes a huge gaffe, and the market price will reflect it in minutes, where a poll aggregator could take days to see any effect.

This is the “social utility” of prediction markets, to answer a question that Chris Masse always poses. While they are on par with the accuracy of the best poll aggregators, their forecasts are real-time and reflect the state of the race right now. No other mechanism does this. While markets are certainly fed by polls, that isn’t the whole puzzle in and of itself.

Prediction markets worked quite well again this election cycle. Though their final forecasts were on par with the best poll aggregators, their real-time forecasts throughout the election season is the reason why they should be examined and discussed more broadly.

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Tomorrow is going to be a landmark day for prediction markets. The 2008 US election cycle has been the most-polled, most-predicted, and likely the most-analyzed election in history. It’s been going for nearly two years, and I for one am glad the election will soon be over and governing (by whomever wins) will soon begin.

But why will it be a landmark day for prediction markets? Simply put: the data.

Prediction Markets and Polls – The Data

There are prediction markets on a wide variety of sites, with both play-money and real-money incentives. Iowa Electronic Markets, InTrade, and Betfair for real-money; HubDub, Inkling, NewsFutures for play-money. There are more, but these are the sites I’ve seen cited most often. (It’s too bad ConsensusPoint didn’t push TheWSX.com this election cycle.)

More importantly, there are a few sites that offer incredibly deep (and also probabilistic) analysis into polls. Most notably fivethirtyeight.com, which I seem to be checking a couple of times a day, now. There are national polls, national tracking polls, state polls, and even some state tracking polls! Fivethirtyeight in particular does deep-level statistical analysis to determine from poll results and demographic data how likely each state is to vote for each candidate.

The number of data points, from different prediction markets, polls, and poll trendlines/analysis will be immense. The sum total of data that will be available after this election should be a treasure trove for researchers, and should finally prove the accuracy of prediction markets.

But there’s a hitch…

Yes, there’s always a hitch, and it’s something I’ve discussed before. In elections, polls and prediction markets are measuring two different things.

Polls are measuring the percentage support for a candidate. Generally around 40-60% or so, unless it’s a total blow-out.

Prediction markets measure the percentage chance that the candidate will win their election. When the election is tight, around 50%, when it’s a blowout can regularly be 95%+. (Few prediction markets exist for candidates’ vote share; really only on the presidential level.)

What should you expect on Election Day?

I expect that a number of news outlets will be quoting percentages from InTrade in the run-up to the end of polls closing in the evening. Already final results contests are springing up, including one in the New York Times where you earn points based on current InTrade odds. You can also expect a LOT of volume on the markets tomorrow. But once the results start rolling in, the news is going to focus on the candidates alone. Wednesday will start the morning-after evaluation of the polls and markets, which will likely last for quite some time.

What does this mean in the end?

Comparing the results of polls and prediction markets is certainly like comparing apples and oranges. There are certainly some similarities, but they are fundamentally different.

What we need to do is evaluate how each forecasting method performed independently. For prediction markets, that means that a “failure” (where a prediction >50% didn’t happen) is quite likely a success. For polls, that means that a result just a few percentage points off (outside its MOE) is a failure.

I believe that prediction markets will come out looking quite good in this election. They’ve already proven their worth to me; when poll results might indicate a close or tightening race in places, the prediction market magnifies the difference, and in many cases demonstrates the poll volatility is just noise.

In the end, are the results from the prediction markets useful? Based on the number of times I’ve seen them cited this year… the answer is an unqualified YES. Are they perfect? No, and neither is any other forecasting system or technique.

I’m really looking forward to tomorrow…

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• First, a great post from Koleman Strumpf on Midas Oracle points out that half of all trades on the Betfair exchange in 2004 occurred on Election Day! While I personally think that was quite likely due to the early exit poll news for Kerry and the subsequent swing back to Bush, it proves that there are still quite a few people that may be waiting until the very last day to trade.
• Jason Ruspini just started a new thread on the Prediction Markets e-mail group regarding some divergences he’s seen between prices on InTrade and fivethirtyeight.com.

  While I think some of the things he’s observed is due to the way Nate Silver presents data on his site, Jason brings up a very good point. A thorough analysis of movement in the InTrade prediction markets should be compared to the daily calculated win percentage from fivethirtyeight (where all data comes strictly from polls). I think it could be very revealing, and give the public quite a bit more data on the accuracy of polling, aggregation of polls, and prediction markets.

• A long time ago I started four different markets on Inkling Markets that will hopefully predict control over each house of Congress, and the number of seats each party will have after the election. Data is shown here:
  
  
  (as I write this, the Democratic percentage is 53.8%, which corresponds to 234 seats in the House of Representatives.)
  
  
• I may need to update my post on prediction market software soon. Xpree (founded by Mat Fogarty, and recently joined by Leslie Fine, a well known prediction market researcher from HP) may be changing their name. The top three picks according to their contest on NameThis were:
  1. Metricast
  2. UREprojection
  3. Keymet

  Personally, I don’t like #2 or #3, but Metricast sounds interesting. It also sounds like a much better fit to what they do than “Xpree.”

  Good luck to them, if they choose to go down this route.

• Do you speak Danish? Nosco is hiring!
  For English speakers, so is InTrade and Xpree.

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Obama on InTrade

The recent nomination of Sarah Palin as Republican VP candidate seemed to have changed the dynamics of the race, and she has certainly sucked up quite a bit of media attention (both positive and negative).

What I find curious is the results on the InTrade prediction markets. Specifically, over the past day and a half there have been some really interesting swings on the Obama (and McCain) contracts.

I can absolutely understand that the candidates are getting closer. But Obama dipping below 50%, and then McCain going above Obama are pretty big steps! I’m surprised they happened without a particularly major event taking place. That said, I have a few reasons/thoughts:

• Manipulation: It’s certainly not unknown, but is certainly hard to detect. (Because it comes down to intention instead of action). But when I read Mike Linksvayer’s post at Midas Oracle noting that the Obama-President and DemNominee-President weren’t consistent, I do tend to think that it might be an irrational or potentially manipulative trader. That said, at least on InTrade the two contracts are now about equivalent for McCain, but about 2.5% different for Obama.
• Trader bias: In the discussions to Mike’s post, Nigel makes a good point that other real-money exchanges (such as Betfair and the Iowa Electronic Markets) still show Obama as a favorite. IEM currently has the Winner-Take-All, aka probability market, at 55/45 Obama. Are the traders on InTrade biased somehow? (Again, this could link back to manipulation depending on their motivations).
• Volatility: I’ll admit, I don’t check InTrade on a daily basis. But that said, it seems that the presidential contracts are quite volatile right now. Considering that no major events have been happening recently, I find it a bit odd that we’re seeing five-point swings in the matter of hours. Perhaps there is an extra sensitivity around the 50% price-point?

Minnesota and the IEM

Iowa is right next door to Minnesota (the state where I grew up), and Minnesota has a hotly contested election for a seat in the US Senate up for grabs this year. The Republican incumbent is Norm Coleman, and the Democratic challenger is comedian/radio-show-host Al Franken. Iowa Electronic Markets set up a market for this race, which I haven’t seen marketed particularly widely. Then again, it’s largely local/regional interest.

I find the difference between the IEM prices and InTrade to again be interesting in this market. In the local and US-legal-without-question market on the IEM, Coleman leads Franken 62/38. On InTrade, Coleman leads Franken at 57/43. There looks to be a more volume dollar-wise on InTrade, but IEM potentially has more local knowledge here.

Should be interesting to follow this in the next couple of months and see how and when the markets converge.

exchangeP

If you’re reading this blog, I figure there’s a decent chance you would have heard about TechCrunch and the TechCrunch50 conference. Fifty startups launched and demo’d their new sites and technologies over three days.

I got a kick looking at exchangeP. (Check out their site with demo video here.) Essentially they have created a niche prediction market site to determine the valuation of private companies, such as Facebook, LinkedIn, etc. While they describe it as a fantasy stock market, it’s really a fantasy prediction market since each “stock” is eventually cashed out.

Part of me is a bit incredulous that a site like this managed to get accepted at a conference like TechCrunch. Turning it into a profitable business seems to be something that they weren’t really considering.

But what really impressed and amused me was Mark Cuban’s feedback to them. (You can see it on the video.) The correct and impressive insight is that he remarked that it would never be big enough to turn it into a real-money site, so it wasn’t really viable as a business that way. Amusingly, he recommended that since they’ve already built their market tool/technology that they could then become a provider of technology for all of the people/companies that want to start prediction markets of their own.

So perhaps I’ll be adding them to my list of prediction market software vendors soon? Then again, they probably don’t know the diversity of prediction market software vendors out there today. From my first look at their site, it looks sub-standard.

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