Common pitfalls of enterprise prediction markets: participants who lack relevant information, too few participants, and too little trading.

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&#8220-Prediction markets seek information aggregation from a large group of diverse individuals by encouraging active participation.&#8220-


&#8220-The biggest challenge is getting people in the company to be active&#8221- [].

Robin Hanson cant ignore Paul Hewitt anymore.

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Spot the comments in the following posts:

Robin Hanson to Paul Hewitt &#8211- #1

Robin Hanson to Paul Hewitt &#8211- #2

Robin Hanson to Paul Hewitt &#8211- #3

Previously: The Robin Hanson manipulation papers make unrealistic assumptions, but it’s not like prediction markets are a bad idea…!!…

Does information economics apply to prediction markets?

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Who is Paul Hewitt&#8230- and what the hell is &#8220-information economics&#8221-&#8230-!??&#8230-


About Paul S. Hewitt, B.Comm, CA

I am a Chartered Accountant with a public practice in Toronto, Canada. While much of my work involves personal and corporate income tax, my practice consults with corporations to improve their business planning processes. I am a graduate of the University of Toronto, with a B.Comm degree, but this is somewhat misleading. A significant portion of my course load was focused on economics, and in particular, information economics. Then, it was a relatively new branch of economics, and it had yet to become overly bogged down by theoretical calculus! In short, it was fun. I wrote an undergraduate thesis: “A New Theory of the Economics of Discrimination.”

Then, I moved on to the corporate world, obtaining my CA designation while working at Price Waterhouse in Toronto. Several years later, I branched out on my own, developing a public practice primarily focused on tax consulting.

&#8220-Information Economics&#8221-:

Information economics or the economics of information is a branch of microeconomic theory that studies how information affects an economy and economic decisions. Information has special characteristics. It is easy to create but hard to trust. It is easy to spread but hard to control. It influences many decisions. These special characteristics (as compared with other types of goods) complicate many standard economic theories.

The subject is treated under Journal of Economic Literature classification code JEL D8 – Information, Knowledge, and Uncertainty. The present article reflects topics included in that code. There are several subfields of information economics. The first insights in information economics related to the economics of information goods. In recent decades, there have been influential advances in the study of information asymmetries and their implications for contract theory. Finally, with the rise of computers, economists have begun to study economics of information technology.

The starting point for economic analysis is the observation that information has economic value because it allows individuals to make choices that yield higher expected payoffs or expected utility than they would obtain from choices made in the absence of information.

I like that. For those interested in more, Paul tells me that the Toronto Public Library has freed some academic papers on information economics. E-mail him for more info.

Does information economics apply to prediction markets?

  1. Information generated by our prediction markets is easy to create but hard to trust.
  2. The market-generated predictions are easy to spread but hard to control.
  3. They influence many decisions.

I think that only #2 is true &#8212-and #1 is half true (although I could also say it is true, too, I am not really sure about that one). The fact that #3 is untrue infirms the Hanson approach. Your comments?

Paul Hewitt on enterprise prediction markets

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– Here, in response to Jed Christiansen. (Scroll down.)

– Here, on his own blog.

Interesting. (Paul should learn to pepper his posts with external links, though. Otherwise, a web visitor out of the loop can&#8217-t get the background of an issue that is discussed. The foundation of the Web is hyper-linking, Paul.)

Who needs pundits track records when we have prediction markets?

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Emile Servan-Schreiber:

Mr. Kristof, if you want to keep yourself accountable and track the success of your predictions in the long run and in real-time, why not simply participate in a prediction market such as NewsFutures?

You could suggest that particular stocks be listed in relation to particular new stories and their possible outcomes. Then, as you invest in particular outcomes, your prediction portfolio would either grow or shrink, providing us all with an objective measure of your foresight. You could feature on your blog a widget displaying in real-time the &#8220-net worth&#8221- of your various predictions.

Other advantages of this approach would include:

Forcing a detailed specification of possible outcomes-
Having you compete directly (bet against) the general public-
Measuring how much your columns can influence price movements for various predictions-
Leading by example to show other pundits how it&#8217-s done.

There are various types of prediction markets out there, so you can pick the venue where you&#8217-d feel most comfortable:

– Play-money only, like NewsFutures– [or HubDub :-D ]
– Real betting (illegal) like Intrade-
– Charity-driven, like Bet2give.

If the idea intrigues you, please contact me at [email protected] and we can get you started right away!

Emile Servan-Schreiber
CEO, NewsFutures


Readers, do click on the link (which will bring you to the New York Times), and do click on &#8220-Recommended&#8221- under Emile&#8217-s comment &#8212-so that his pitch for the prediction markets will be more visible to all the people reading the comments there. Thanks. Appreciated.

WeatherBill can be thought of a) as expressive insurance b) as a combinatorial prediction market with an automated market maker.

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This clarification from our good doctor David Pennock shows how indispensable this research scientist is to small people like us. :-D Without David Pennock, the field of prediction markets would collapse like a castle of cards. Ha! ha! ha!&#8230-

As a blogger, WeatherBill presents a difficulty: How to you categorize it? I fill it in these 4 categories:

  1. insurance (obviously)-
  2. finance (because it is hedging)-
  3. exchanges (because of what our good doctor Pennock said above, see the title)-
  4. betting (because the reverse of hedging is speculation)-
  5. UPDATE: I just added &#8220-hedging&#8221- &#8212-so that&#8217-s 5 categories now, probably too many. (It probably shows my readers that I am confused&#8230- and really need a &#8220-research scientist&#8221-. Ha! ha! ha! :-D )