On prediction markets

"Chris Masse is a mean-spirited snob who obsesses with bloggers' prediction markets, which is a concept he's totally incapable of explaining clearly..."

Well, I don't believe that statement but he DID dare someone to write it, and it's hard to resist a snarky dare. Now to the main point of this post:

Over at Chris F. Masse's blog, he's been discussing the role of certain start-up prediction markets, specifically CrowdIQ and Inkling. For the most part, he's been fairly negative towards them as he doesn't see much useful purpose in how they open their systems for most anyone to create a market. Specifically, he writes with dripping sarcasm: "Inkling Markets and Crowd IQ have persuaded themselves that user-created prediction markets are going to be a worldwide phenomenal success, to which the public adoption of the telephone in the last century will compare palely."

In some ways, I agree with him. User-created markets tend to be pretty poor. There are simply too many people acting as market makers that just don't understand how prediction markets should work. Perhaps more critically they are asking questions poorly. (I believe there was one market on Inkling for who would win a particular World Cup match, but there was no trade option for a draw!) Some markets makers also don't understand how to properly pay out a contract, which has led to some problems according to some user forums.

However, I think he's missing a bit of a bigger picture on why these companies exist. Right now they are still developing their software. By throwing their doors open wide and letting a variety of people create markets and trade, they get a crash-course in what works and what doesn't in their software, and more importantly what users value and what they don't value. To me, this is the reason why they are marketing their "user-defined" prediction markets so heavily. They're doing exactly what Guy Kawasaki recommends innovators do: "Ship, then test," "Don't worry, be crappy," "Churn, baby, churn," and "Don't let the bozos grind you down."

To imply (as Chris Masse has) that this define their entire business model is incorrect. To me, the user-defined markets are the "loss-leader" that get people interested in prediction markets, and serve as a testbed for their software. Clearly where they think they're going to make money is from corporate prediction markets. (CrowdIQ mentions this purpose, and Inkling is marketing its use on their front page.) While I'm not privvy to any of their business plans or strategies, this would clearly make the most sense.

I would love it to get even more companies out there developing prediction markets. The more, the merrier! Let everyone fight it out in the marketplace to see what users want, what they're willing to pay for, and what exactly is the value of a prediction market to the people that are willing to pay for it. The field is in its infancy; there is a lot left to be developed.

In response to his question about blogger-created prediction markets, that probably is the way that small-scale prediction markets will get sufficient volume to succeed. Bloggers have a specific focus (ie, politics, technology, etc.) and if they feed their readers to a prediction market, that market would have a much better chance of succeeding because of the user's interest level in that focus area. Specifically, blogs like Slashdot or Guy Kawasaki's blog could drive some interesting markets in their field. (Though I would suspect that the diversity of some blogs could limit their success; for example, a Democratic or Republican blog that creates a prediction market for an election could potentially be significantly biased.)

Finally, for full disclosure's sake, I am doing my graduate school project with Inkling. Please see my previous posts below for details, but my research will hopefully investigate how small prediction markets can get and still provide valid results, as well as investigate the types of trading behaviours that make a prediction market successful.

Cheers,
Jed

Research project in motion

I've discussed this briefly on the Prediction Markets Google Group, but I am currently conducting some primary research in small-scale prediction markets. Specifically, I'm looking to determine how accurate the results of prediction markets can be, and what behaviours cause these results.

To be specific, I am running prediction markets in a very niche sport: rowing. Why? Well, I'm on a tight timeframe and this fits in well with my interests and fits my timeframe available to complete my paper perfectly. I expect that some people may find fault in my methods since the markets are sports related, but I think I've minimised any distinction here. First, you'll be hard-pressed to find a bookmaker that publishes odds, unlike football, horse-racing, etc., so the same kind of widely published betting information doesn't exist. Second, the competitions are races so there aren't issues with teams fouling or otherwise interfering with each other. Third, there is near-zero media coverage outside of someone who participates in the sport.

Here are some of the issues I expect to address:
* How accurate are the groups predictions?
* How accurate are predictions relative to the number of traders in the market?
* What types of behaviours do traders exhibit?
* How do price manipulations affect small markets?
* How do behaviours influence the success of a market? How does this relate to the number of traders in a market?
* (potentially) How accurate are the groups predictions relative to expert predictions?

By the middle of July, I expect to have completed in excess of 60 individual markets, each with anywhere from 2 to 15 stocks. This should be sufficient data to make some interesting observations. Most stocks trade in the $0-$5 range, though a few get up to the $60-80 range.

I am doing this research with Inkling Markets. In my anecdotal working with amateur traders, I've found that most people are not fluent in trading techniques, and the user interface they have developed is one of the best I've seen. That, and the instant liquidty makes much more intuitive sense for novice traders.

This is the reason it has been quite some time since I've posted here; the project has taken up much more time than I anticipated! (And for that matter, continues to take up more time than I anticipated.) If anything, the only problem I have is that my marketing of these markets was perhaps a little too good, and I'm getting more people than I ever thought I would get participating. This result is still far better than the reverse, however.

I will publish preliminary results here as I compile them.

Cheers.