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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Theme 1 – Software vendors moving up the value chain

The biggest theme to me is that the traditional software vendors (ConsensusPoint, NewsFutures, Crowdcast, Inkling Markets) have all been moving up the value chain. Where they used to provide software, they all provide a much more consultative service as well. For example:

• Newsfutures, which always had a much more consulting-style approach, merged with another consulting group to become Lumenogic. Prediction market software is hardly mentioned; they pitch consulting and strategy.
• Consensus Point has hired additional senior people, and David Perry has left. Their pitch features the consulting services much more prominently than it did in the past.
• Crowdcast has been trying to go even bigger, taking venture capital investment. And like the others, features more “solutions” than just licensing software. (Leslie Fine was a terrific hire for Crowdcast, and board member Dr. Andrew McAfee is a top thinker in the “Enterprise 2.0″ movement.
• Inkling Markets still has a great angle in the market. They appear to be a go-to company to run pilot prediction markets, and are then perfectly positioned to establish a long-term relationship if/when the trials go well. I get the sense that they tend to do less consulting work than the other companies, but will do so for larger clients. I also want to make a special mention of Inkling’s blog, which is the best one of all the prediction market companies.

Theme 2 – Free (broad) prediction markets can’t survive alone

If you think you can build a strong business on a free prediction market, you’re kidding yourself. HSX, which is great, it’s focused on a single industry and even then it’s an outlier. It exists because they’ve built a solid business selling analysis to movie studios. (Alex Costakis, the long-time CEO, left this year after Congress made it clear trading movie futures wasn’t going to happen. This meant that Cantor Fitzgerald had little reason to keep investing in trying to make a load of cash from extending HSX to do this.)

HubDub, a more generalist/news prediction market, was completely shut down because it wasn’t going to make enough (or really, any) money. Nigel, Lesley and team changed focus to fantasy sports and they seem to be doing quite a bit better.

So while I believe that very niche prediction markets associated with particular industries can thrive, it takes a lot of work to build a real business from it. And broad-based prediction markets aren’t going to make anyone any money, though they could be an investment to build traffic. (HubDub had a lot of user engagement, they just couldn’t build their prediction market into a business.)

Theme 3 – Real-money prediction markets (aka betting sites) are going strong

BetFair IPO’d in October of this year, (BET) and had targeted a £1billion market cap. They’re a very strong business, and are very well positioned if/when the US legalizes any form of betting or online gaming.

Smarkets is a startup in the betting/prediction markets market, and just recently passed £2million traded on the site. (They grew from £1million to £2million much more quickly than they grew to their first £1million.) I’ve known the CEO, Jason Trost, since he and his co-founder Hunter were doing the initial coding and fundraising in their London flat. They have a very bright future ahead of themselves.

Contrary to broad-based play-money markets, real-money betting has a solid business model that scales to become a big business. They are long-term businesses.

Summary – A market maturing

In short, the prediction market industry is maturing. I’m not naive; it’s a small market outside of the real-money betting markets. There is a solid core of strong businesses that have established themselves as the source for software and consulting and I see them continuing to grow as more companies experiment with new management tools and techniques. Niche play-money markets may also thrive, though this still remains difficult to execute.

I foresee that 2011 will be very similar to 2010: more mature and developed solutions from the established prediction market companies. It’s less interesting from an outside perspective, since there doesn’t appear to be much change. But internally I believe these companies will be an interesting place to be as they grow and work with increasingly more interesting and blue-chip clients. (And as I already said, Smarkets has a very bright future ahead of themselves in the real-money betting industry!)

I hope everyone in the industry has a happy new year and my absolute best wishes for 2011.

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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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About a year and a half ago, my blog was hacked. I was notified of it by Google’s webmaster tools, and it took quite a while to go through all the different files to find the offending code and strip it out. It ended up being located in a number of different places, so it took a few go-through’s re-submitting the site to Google before the hack-detection software declared it clean.

I was always a little worried that I hadn’t gotten it all. Recently, I came across a great couple of blog posts that I highly recommend:

• This is a good general description of why you need to be worried and links to a couple of tools you can use.
• This is a link to a WordPress plugin called “Exploit Scanner.” I uploaded it to this blog and found a number of files that were clearly hacker-installed. I’ve since un-installed them, but want to post some things to help anyone else that might face the same situation in the future.

———————-

Files that were uploaded:
fx_akismet.php
fx_blogger.php
fx_I10n.php
fx_menu.php
fx_wp-config.php
fx_wp-db-backup.php
… and a folder of 70 html files and a javascript file meant to steal Google PageRank

All the php files were nearly identical. Here’s the code:

I don’t code in php, so I don’t really know what this says, but hopefully it might be useful to anyone afflicted by the same script.

I highly recommend if any of you have WordPress blogs to take these same steps to see if you’ve been hacked.

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Basecamp is used a lot in small and medium businesses, and I’ve heard that it’s becoming more common in niches of larger businesses. (It’s easy to put the relatively small monthly bills on corporate purchase cards.) It’s popularity means there’s a great population of potential customers that can start taking advantage of this new source of information.

(Inkling’s full post on how to implement prediction markets within Basecamp can be seen by clicking here.)

I’ve written before that I think there is a LOT of value in using prediction markets to forecast project milestones. (It’s generally done poorly, if it’s done at all.) One of my more popular posts according to Google Analytics is “RAG status – people lie, prediction markets don’t“. I dreamt of a day where prediction markets would be run on all project milestones, and the results of those markets would drive a project’s “RAG status”. That is now easily done with Inkling’s Basecamp widget.

There are probably still a few details to be ironed out with the actual implementation, but this is a great step forward for businesses that want better intelligence from their employees and partners. I look forward to hearing more from Inkling about how customers have taken advantage of this and if/how it’s worked for them.

From their blog post, here are two screenshots of what the screens look like before and after you trade:

The “trading” screen:

The results screen:

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I’m a little partial to these guys, mainly because they come from my alma mater, the University of Michigan. The key people look to be a mix of entrepreneurial students and professionals. The company itself was started a year and a half ago, but has had success with early pilot projects.

In fact, three slides included in their “Learn more” online slideshow are quite powerful statements as to why prediction markets can be useful. They were predicting car sales in the winter of 2008/2009, during what was one of the most volatile months the industry has seen in many, many years. And the prediction market beat the internal forecast made at the beginning of the month, and the expert forecast made at the end of the month.

Here are the slides:

To recap, the prediction market beat the official GM forecast (made at the beginning of the month) easily, which isn’t hugely surprising considering the myopic nature of internal forecasting. But the prediction market also beat the Edmunds.com forecast. This is particularly interesting, as Edmunds would have had the opportunity to review almost the entire month’s news and data before making their forecast at the end of the month.

Examining the numbers

Let’s quickly quantify this error. Assume an average Chevrolet sells for $18,000. After dealer markup, assume that GM/Chevrolet receives $16,000 per vehicle.

Within the first week of November 2008, the prediction market would have warned Chevrolet that they were going to miss their revenue targets by $800 million in the Chevrolet division alone. And depending upon the exact product mix, this could have easily exceeded $1billion.

Now Chris can blather on about corporate prediction markets, but he’s simply wrong. Assume that even with three weeks’ early warning Chevrolet was only able to save 10% of that gap, it’s still $80million in savings. Even if a corporate prediction market for a giant company like GM cost $200,000 a year, that would still be a return on investment of 40,000 %. And again, that’s in the Chevrolet division alone. (Note: It would be a rare prediction market that cost $200k/year to run.)

Now not every problem should be solved by a prediction market. This is where management expertise comes in: are the errors large enough to warrant the cost of reducing those errors? But big problems with big numbers are often very suitable to address with a prediction market.

Summary

I’d like to wish good luck to the CrowdClarity team. It’s great to see Wolverine entrepreneurs working on prediction markets. There are more and more players each year in the corporate prediction market scene, but with case studies like this behind their belts, they’ll be well-placed to pick up some business.

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Y Combinator is a very unique seed accelerator program. Startup companies get ~$15-20k in funding in return for ~6% equity, three months of intensive business and product advice, connections to mentors and potential advisors. Inkling Markets was in the second cohort of Y Combinator funded companies, for example.

My hypothesis was that a lot of people/organizations are starting seed accelerators without really examining the full scope of innovations they need to think about in order to achieve their goals. I wanted to take the opportunity to look into why entrepreneurs choose to go into a seed accelerator, why individuals choose to start a seed accelerator, and then propose a framework for designing new programs.

You can click here to view the post on my personal blog that has a bit longer executive summary. But I’ve embedded the paper and data sources below. I hope you find it interesting.

Copying Y Combinator

Appendix A – List of Seed Accelerators

Click here to view the list of seed accelerators. Only seed accelerator programs are listed; see main paper for details.

Appendix B – Example Seed Accelerator financial model

Appendix C – List of all companies founded by Seed Accelerators

OR

Click here to view the list via Google Docs.

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Chris Masse over at Midas Oracle has recently generated a fair number comments on his post “Are IBM Smarter Cities prediction markets too smart for people?” As the commenters rightly point out, what IBM was doing was NOT a prediction market, but instead a polling system.

This is something I’ve been talking about since May 2008. When you try to use a prediction market to forecast the “best” ideas, you get a “Keynesian beauty contest.” To quote (via wikipedia):

It is not a case of choosing those [faces] that, to the best of one’s judgment, are really the prettiest, nor even those that average opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. (Keynes, General Theory of Employment Interest and Money, 1936).

Starting from the wrong metaphor

Ideas in an organization are a long-term investment, where significant work and development is required before you can even get to the prototype stage of development. This is a very different concept than regular, known markets, such as the number of customers in the next quarter or “will me meet sales targets next year” which are asked in prediction markets. Prediction markets work well for the regular, known markets, because prediction markets involve liquid, easily-traded contracts.

Idea markets should be seen through the metaphor of venture capital. An individual sees lots of good ideas, but none of them are well developed. Just as a venture capitalist puts resources into ideas and those resources are locked-up and illiquid until the idea has proven its success or died, an individual in an idea market should see their votes as an illiquid, sunk cost.

The organization running the idea market then concentrates their resources where individuals concentrate their votes. But just like venture capital, this cannot be a one-time market. The organization needs to regularly run similar markets, say every quarter or every six months. If an idea gets resources but doesn’t make enough progress (or doesn’t look like it will be as effective as originally thought) the market will stop voting for it. As an idea makes good progress, it continues to receive resources for development. Finally, when an idea is implemented and made successful, all of the people that voted for it during its development will be rewarded. And just like venture capital, the earlier you contribute the more you are rewarded.

The key is that idea selection and development is long-term work, and thus when markets are used to forecast and help allocate resources, the market structure must match that long-term approach.

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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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From Emile of NewsFutures, here are three links and a quote from each:

The imagination market, Information Systems Frontiers (July 2007)

Participants were able to trade shares of technology ideas over the course of 3 weeks, resulting in the market identifying the “best” idea as the highest priced security. Our findings suggest that information markets for idea generation result in more ideas and more participants than traditional idea generation techniques; however, using markets to rank ideas may be no better than other methods of idea ranking.

Examining Trader Behavior in Idea Markets: An Implementation of GE’s Imagination Markets , Journal of Prediction Markets (April 2009)

In this experiment, we examine the behavior of traders that have submitted the ideas on the market and their influence on the market’s outcome. An idea’s submitter is clearly motivated to have his idea valued highly by the market, both by the funding given to the top idea as well as smaller prizes given to the top three ideas. In general, founders tended to buy their suggested ideas at prices above the volume-weighted-average-price (VWAP) in significant volumes. We discuss the implications and mitigation strategies. A survey of market participants yielded mixed results regarding the market’s effectiveness at ranking ideas but very positive results regarding the quality of ideas proposed.

GE Global Research blog (link here)

From the comments,
“GE Healthcare IT attempted an imagination market a few months ago to bring forth some new ideas for the company’s future. It left me with very strong mixed impressions: on one hand, it’s wonderful that we’re leveraging the power of technology for mass collaboration and idea sharing. On the other hand, I felt that the tool obfuscates the very opinions it seeks to gather by due to the inherent complexities of market behavior.

My primary objection is the use of the stock market paradigm to evaluate these ideas. Simply, I find it too abstract to be useful in gathering feedback about the quality of an idea. Stock investment is done by trying to predict *the change in collectively perceived value of something over time*. However, when dealing with ideas, neither the collectively perceived value, nor the change in this value over time are valuable metrics; you want people evaluating ideas based on *their opinions*, not based on their attempts to predict changes in the investment decisions of others over the course of a few weeks. These are static ideas isolated from one another, not evolving companies that interact. I think a stock market is an unnecessarily abstract, and distracting way to retrieve simple information: what do people think of these ideas?”

I’d be interested in hearing from people that disagree with this…

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