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In my previous post on categorizing prediction markets, one of the key differences is whether a market is public or private. (The “P” in the ICROP criteria.) There is fundamentally a very different value to the operators of a public market compared to a private market. My train of thought is below, starting with some notes on recent prediction market news.

Recent news from Hubdub

Hubdub recently announced a partnership with Reuters, which I think is a great step for public prediction markets. They previously had announced a partnership with the Huffington Post blog. When that was announced two weeks ago I was a little torn of what to think. It was great they were able to work with a major internet brand, but the implementation was pretty weak. You could find Hubdub’s markets on Huffington Post tag pages, but even knowing it was there I really had to search to find them on the page. It seemed to be something that was being treated as just a minor experiment rather than something serious.

The Reuters announcement is much more important. It looks like it’s kicking off a wider partnership program at Hubdub, which is quite exciting. Reuters has a dedicated section on the Hubdub site which will apparently be regularly updated by Reuters staff. (They’ve only created 4 questions so far.) The only scheme that I think would be better than this is if Reuters had put a dedicated Hubdub section on their (Reuters) site, and that could certainly happen down the road.

By opening up Hubdub to a wider partnership program, they will help other companies and bloggers build a reputation by allowing those people and organizations to generate interesting questions and predictions. This is great news, and should spur even more growth for both the participating bloggers and Hubdub itself.

But this got me thinking about public versus private prediction markets…

Value in Public versus Private markets

The value to operators of public markets is significantly different than private markets. I think this is why we are seeing significantly different types of growth in the two types of markets.

The value to operators of public markets comes from generating an active, thriving community of users. These users may be targets for advertising, subjects for demographic research (HSX), see examples of technology (Inkling, NewsFutures), or another unique model to be determined. This is where Hubdub looks to be pioneering.

Nigel Eccles, the CEO of Hubdub, has mentioned on many occasions some interesting statistics about an average subscriber’s interaction with a newspaper’s online presence. For most newspapers it is extremely limited; a person will check a story or two and leave. There is little real engagement, and so page views and advertising rates aren’t as high as they could be. (Alex Kirtland talked about this here.) However, prediction markets have shown themselves to be hugely engaging, and can also be made highly local and relevant to a small audience. This looks to be the way they’re going with their partnership program. Each partnership will add and build another sub-community of users, which adds value to both the partner and Hubdub.

The value is significantly different for private markets. When I think of private markets, I think of a corporate prediction market where the company is looking to get useful and accurate business intelligence from their employees. The business intelligence is the value many companies claim they are trying to capture.

The difficulty in private markets is that there is no obvious, traceable value chain. In that I mean that most companies cannot say that because the market told management that there was X% chance of event A occurring, the company changed strategy and saved $Y. Many companies are in reality treating them as non-actionable market intelligence, where they examine only after the fact how accurate the predictions were.

Even if a company did trust their employees enough to take action directly based off of what their internal markets were telling them, it may still be difficult to calculate the value of that intelligence. Particularly since management wants to be (or at least appear) smarter than their employees, it is quite easy to claim after the fact that they would have taken the same actions based off of other intelligence.

Fundamentally, it takes a company that both trusts their employees enough to take action on the market indicators and management that is honest enough in what would have happened without that intelligence in order to calculate the value of those prediction markets. For example, Mat Fogarty has talked about how he used prediction markets at EA to quantify game quality scores, which is certainly useful. But where that can directly turn into additional profit is if EA (or any similar company) took prediction market intelligence to adjust how they filled their distribution channels. They could save money by not creating unnecessary copies of bad games, and could make more money by ensuring they had enough copies of hit games ready when they went on sale. As far as I am aware, few companies have taken that final step to action based on market results.

Prediction markets certainly add value even where the elements I mentioned above aren’t present, it’s just that the direct value cannot be easily calculated. And until an executive can directly point at how the cost of a prediction market is more than made up by the direct value added, the growth of prediction markets will be limited.

That said…

Prediction markets are clearly a growth industry, even in private markets. Inkling Markets, NewsFutures, and Xpree have all recently hired great new people into their businesses, so the market for private markets is clearly growing. But until the value calculation above can be directly made, that growth rate just isn’t as high as I wish it would be.

(Gratuitous photo is from a recent holiday, specifically a section of the Great Wall of China outside of Beijing.)

I’ve got a few posts coming soon on the innovation topics I’ve been discussing more recently, but prediction markets have really been the hot topic with the current election. Here are a few issues I find interesting:

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.