Lets use Google Wave to interact with all the prediction market fanboys.

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  1. chrisfmasse
  2. ++++++AT++++++
  3. googlewave
  4. )))DOT(((
  5. -com-

I am trying to learn how to use Google Wave. First impression: Very weird.

For the Google Wave invite, I thank Martin Frindt of http://www.crowdpark.de/.

UPDATE: Jed says I will get the invite wave in a few days. Patience. I will then be able to invite friends of mine.

Please, be my friend on FaceBook.

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Our good friend George Tziralis has 505 friends on FaceBook.

Our good friend Mike Linksvayer has 762.

I have only 61.

I feel ridiculous. I am sure people laugh at me in my back about that low number. I need to have at least 100 friends. Help me.

P.S.: I have been focusing more on my LinkedIn network. See the sidebar for all our PM networking links.

The truth about (enterprise) prediction markets

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Paul Hewitt:

[…] In virtually every case, the prediction market forecast is closer to the official HP forecast than it is to the actual outcome. Perhaps these markets are better at forecasting the forecast than they are at forecasting the outcome! Looking further into the results, while most of the predictions have a smaller error than the HP official forecasts, the differences are, in most cases, quite small. For example, in Event 3, the HP forecast error was 59.549% vs. 53.333% for the prediction market. They’re both really poor forecasts. To the decision-maker, the difference between these forecasts is not material.

There were eight markets that had HP official forecasts. In four of these (50%), the forecast error was greater than 25%. Even though, only three of the prediction market forecast errors were greater than 25%, this can hardly be a ringing endorsement for the accuracy of prediction markets (at least in this study). […]

To the despair of the Nashville imbecile, Paul&#8217-s analysis is quite similar to mine (circa February 14, 2009):

The prediction market technology is not a disruptive technology, and 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.

Prediction markets are not a disruptive technology, but merely another means of forecasting.

Go reading Paul&#8217-s analysis in full.

I would like to add 2 things to Paul&#8217-s conclusion:

  1. We have been lied to about the real value of the prediction markets. Part of the &#8220-field of prediction markets&#8221- (which is a terminology that encompasses more people and organizations than just the prediction market industry) is made up of liars who live by the hype and will die by the hype.
  2. Prediction markets have value in specific cases where it could be demonstrated that an information aggregation mechanism is the appropriate method that should be put at work in those cases (and not in others). Neither the Ivory Tower economic canaries nor the self-described prediction market &#8220-practitioners&#8221- have done this job.

250 members of the LinkedIn group on prediction markets

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1. How To Join Us

  • From within LinkedIn, FaceBook, or Google Reader / Google Mail, send me (Chris Masse) an invite and I&#8217-ll accept it.
  • You are also invited to join the Prediction Markets group at LinkedIn. We accept everybody (traders, analysts, researchers, consultants, exchange managers, bloggers, etc.).
  • [As for joining Midas Oracle as a commenter or poster, see this other webpage.]
  • I can introduce you to another member of our business network. Just ask me (Chris Masse), and I&#8217-ll do.

2. LinkedIn Network

For your information, here is the listing of the co-managers of the Prediction Markets group at LinkedIn:

  • Jed Christiansen of Mercury
  • Tony Clare of BetFair
  • John Delaney of InTrade
  • Nigel Eccles of HubDub
  • Chris Hibbert of Zocalo
  • Chris Masse of Midas Oracle
  • David Pennock of Yahoo! Research
  • Michael Robb of BetFair
  • Emile Servan-Schreiber of NewsFutures
  • Adam Siegel of Inkling Markets

– The ownership of the group could be transferred to the yet-to-be-created &#8220-Prediction Market Institute&#8221-, at one time in the distant future.

Once you have joined our Prediction Markets group at LinkedIn, here&#8217-s how to make its logo visible on your profile.

– After you have joined our Prediction Markets group at LinkedIn, please make its logo visible on your profile. (In your listing of groups you belong to, you should read, near each one, &#8220-change visibility&#8221-. Click on that.)

– You are also invited to join Chris Masse&#8217-s network at LinkedIn.

Our Prediction Market People – (from the two networks listed just above)

– Bernd Ankenbrand (Gexid Manager)

– Paul Architzel (Counsel at Alston &amp- Bird)

– Maurice Balick (NewsFutures CTO)

– Pierluigi Buccioli (Entrepreneur and Betting Exchange Trader- Owner of Bookmakers Review)

– Jason Carver (Entrepreneur and Engineer)

– Yiling Chen (Professor at Harvard University)

– Jed Christiansen (Prediction Market Consultant)

– Tony Clare (Head of Strategic Initiatives at Betfair)

– Norris Clark (Vice-President of Sales at NewsFutures)

– Alexander Costakis (Managing Director of Hollywood Stock Exchange)

– Tyler Cowen (Economics Professor at George Mason University)

– Bo Cowgill (Quantitative Marketing Manager at Google)

– Eric Crampton (Senior Lecturer at University of Canterbury)

– Noam Danon (Qmarkets CEO and Founder)

– Pedro Da Cunha (Exago Markets CEO)

– John Delaney (InTrade CEO)

– Juan Manuel Ducler (Founder, BestChartsOnline.com / Trader &amp- Financial Consultant)

– Nigel Eccles (HudDub CEO)

– Leslie Fine (VP of Market Design at Xpree)

– Matthew Fogarty (Prediction Market Consultant – Xpree CEO and Founder)

– Lance Fortnow (Professor of Computer Science at Northwestern University)

– Nick Garner (SEO / PPC / Search Manager at BetFair)

– Cedric Gaspoz (Research and Teaching Assistant at University of Lausanne)

– Michael Giberson (Energy Economist at Texas Tech University)

– Sean Glass (Founder, Chairman, Chief Strategy Officer at Pikum Holdings)

– Andrew Goldberg (Intern at Media Law Resource Center)

– Robin Hanson (Professor of Economics at George Mason University)

– Chris Hibbert (Software Architect, Project Lead at Zocalo)

– Donna Hoffman (Professor and Co-Director, Sloan Center for Internet Retailing)

– Panagiotis Ipeirotis (Assistant Professor at New York University)

– Max Keiser (Entrepreneur, Journalist, Co-Founder of the Hollywood Stock Exchange)

– Alex Kirtland (User Experience Consultant)

– Ken Kittlitz (Software Architect, Foresight Exchange, Consensus Point)

– Greg Knaddison (Developer and Sys Admin for PingVision)

– Nathan Kontny (Inkling Markets CTO)

– Kriss Monaco (Director of New Product Development at International Securities Exchange)

– Dean LeBaron (Independent Investment Management Professional)

– Heidi Levin (Director of Business Development at Inkling Markets)

– Mike Linksvayer (Vice-President of Creative Commons)

– Rory Mackay (PredictionsMarkets.com Co-Founder and Owner)

– Chris. F. Masse (Founder and President of Midas Oracle)

– Tracy Mullen (Penn State Professor of Information Technology)

– Jesper Muller-Krogstrup (Managing Director of Nosco)

– Sean Park (Founding Partner at Sixth Paradigm)

– David Pennock (Principal Research Scientist at Yahoo!)

– Daniel Reeves (Yahoo! Research Scientist)

– Michael Robb (Communications &amp- PR Executive at BetFair)

– Steve Roman (Financial Analyst at FXCM)

– Mark Rose (Ex-HedgeStreet Director of Product Development)

– Jason Ruspini (Financial Research Analyst, Vice President at Conquest Capital Group)

– Mike Sankowski (Product Development and Market Operations Manager at US Futures Exchange)

– Emile Servan-Schreiber (NewsFutures CEO and Co-Founder)

– Brian Shiau (The Sim Exchange CEO and Founder)

– Adam Siegel (Inkling Markets CEO and Co-Founder)

– Ashish Singal (Capital Markets Professional)

– Erik Snowberg (Assistant Professor of Economics and Political Science at California Institute of Technology)

– Brad Stewart (Reality Markets Founder)

– Brent Stinski (Media Predict CEO and Founder)

– Karim Tahawi (MyCurrency Founder)

– Jason Trost (Co-Founder of Smarkets)

– George Tziralis (Doctoral Researcher at National Technical University of Athens, Co-Founder of AskMarkets)

– Robert Wilburn (Rimdex CEO and Founder)

– Gerry Wilson (YooNew CEO and Co-Founder)

– Justin Wolfers (Professor of Business and Public Policy at the University of Pennsylvania)

– Matt Youill (Chief Technologist at Betfair)

– David Yu (BetFair CEO, Former CTO and COO of BetFair)

– Eric Zitzewitz (Professor of Economics at Dartmouth College)

– Plus, many, many more&#8230-

Other Prediction Market People At LinkedIn

– Russell Andersson (Chief Operating Officer, Third Ave Beach)

– Adrian Asher (Global Head of Security at BetFair)

– Henry Berg (Group Manager on Information Markets at Microsoft)

– Matt Carter (Director of the Advanced Technology Group at BetFair)

– Jonathan Cumberlege (Former Director of Registrations &amp- Payments at BetFair)

– Gerard Cunningham (President at BetFair USA)

– Mark Davies (Managing Director of Corporate Affairs of BetFair)

– Mike Dooley (Vice-President of Engineering at NewsFutures)

– Sean Dunbar (Former Head of Technology at Hollywood Stock Exchange)

– Mathias Entenmann (Exchange Managing Director of BetFair)

– Brian Galebach (Freelance Computer Programmer and Owner of Probability Sports)

– Carol Gebert (Former Founder at Incentive Markets)

– Christian Hellmers (Director of US Business Development of BetFair)

– David Jack (TradeFair Director)

– Richard Jaycobs (Cantor Exchange Project Leader)

– Nicholas Jenkins – Nick Jenkins – (Owner of Betcha.com)

– Ajit Kambil (Global Director at Deloitte Research)

– Alam Kasenally (Xpree CTO)

– Mike Knesevitch (Ex-InTrade Director)

– Dawn Tevekelian Keller (Director, Services Business Group &amp- Prediction Markets at Best Buy)

– Robin Marks (Head of Media at BetFair)

– Hunter Morris (Co-Founder of Smarkets)

– George Neumann (Professor of Economics And Applied Mathematics and Computational Sciences at the University of Iowa, Co-Founder of the Iowa Electronic Markets)

– Scott Page (Professor at University of Michigan)

– Paul Pluschkell (Founder &amp- CEO at Spigit)

– Todd Proebsting (Director at Microsoft, Former Group Manager on Information Markets at Microsoft)

– Linda Rebrovick (Consensus Point CEO)

– Don Reynolds (Site Administrator at NewsFutures)

– Felix Salmon (Financial Journalist at Portfolio)

– Bimal Shah (Product Manager at TradeFair)

– Martin Spann (Professor at the University of Passau)

– Will Speck (Director Business Development &amp- Market Research at Financial Times &amp- FT.com)

– Martin Thompson (Engineering Director at TradeFair)

– Geoffrey Tso (Engineering Manager at Xpree)

– Andrew Twaits (Corporate and Business Affairs Director of BetFair Australia)

– Mark Wood (Head of Programme at TradeFair0

– Plus, many, many more&#8230-

What Panos Ipeirotis didnt tell you

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Panos Ipeirotis depicted my activism to blog about the tone of the news article on enterprise prediction markets published by The Economist &#8212-and its implications. The takeaway that his readers will get is that Chris Masse is on caffeine. :-D

The important information that our good doctor Panos did not tell is that Chris Masse is the publisher of 2 websites (CFM since 2003 and Midas Oracle since 2006) whose main purpose is to list and/or excerpt the news articles, opinion pieces and research papers that focus on prediction markets. Since 2003, I have seen them all &#8212-in all stripes and colors.

So, it is not like I am a gullible newbie just out of the egg. I have a certain expertise in assessing any media piece on prediction markets. And the same thing can be said about Niall O&#8217-Connor (regarding the betting industry, more generally).

Chris Masses InterPol file

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Chris Masse .com:

Chris F. Masse is NOT a Fraud

But come on, would saying he is really be libel? Seems like a rather subjective statement to me in the first place. What is the metric for &#8220-fraud-ship&#8221-, anyway?

Chris F. Masse

Chris F. Masse, of chrisfmasse.com &amp- midasoracle.org, is NOT a fraud. (But he is slightly overweight, and often stinks of elderberries and old coffee.) Styling himself as &#8220-the most forward thinker in the field of prediction markets,&#8221- Chris daily attempts to offer commentary on prediction markets, economics, and related subjects, from his blog, Midas Oracle.

However, as even a casual reader can glean from Mr. Masse&#8217-s writing, he certainly has an axe to grind. Never mind questions as to whether the man might be bi-polar, or why his posts attract so few comments and engender so little discussion&#8230-no, let us concentrate on what Mr. Masse is saying. From the get-go, Chris attempts to drill into the mind of every reader exactly what a prediction market is, and what its uses are. In a few paragraphs located at the top of his blog&#8217-s main page, Mr. Masse attempts to distill his particular views on the utility of prediction markets while simultaneously dissuading any ideas to the contrary, as though all other writing and actual research in the field is a moot point. Only Chris&#8217-s opinions matter, but they must be taken on faith.

And what are Mr. Masse&#8217-s qualifications to make such claims as are replete throughout his writings? He never provides them, conveniently, but this does not stop Chris from criticizing others who have verifiable experience in the &#8220-nitty-gritty&#8221- of prediction markets. Robin Hanson, the &#8220-father of prediction markets&#8221-, is a particular punching-bag favorite, although Chris apparently has a strong aversion to responding to Robin&#8217-s comments when he posts.

Chris, always a master of logic, claims to take conversation seriously, and in a recent post entitled &#8220-It is not about Midas Oracle&#8230- It is about taking part of the conversation about (enterprise) prediction markets on the Web.&#8221- wrote:

  1. If you are an economist, and have nothing to say about the current banking, financial and economic crisis (the worst in our generation), then you don&#8217-t matter anymore.
  2. If you are a prediction market consultant, and have nothing to say about the negative piece from The Economist, then you don&#8217-t matter anymore.

Mr. Masse seems to be a master of the arbitrary, as he has synthesized rationale for obsoleteness based upon reactions to a very short Economist story that did nothing less than report the facts. And obsoleteness according to whom? Mr. Masse, of course.

But perhaps Mr. Masse missed the critical point that the story had nothing negative to state about prediction markets themselves, simply some observations on their adoption. In conclusion, actually, the story contains these two lines:

Yet many pilot projects run so far have shown that junior staff can often be surprisingly good forecasters. Perhaps the best way to find out when prediction markets will finally take off is to ask your employees—using a prediction market.

Chris, that sounds pro-prediction market to me. Or did you perhaps simply need an excuse to take pot-shots at &#8220-economists&#8221- and &#8220-prediction market consultants&#8221- because &#8220-they&#8221- did not share your reaction against fabricated story content that is not there?

Chris Masse gets a vote of no confidence from me. Any further evidence required to diagnose Mr. Masse&#8217-s ineptness in providing a factual discussion of prediction markets can be found at his blog, Midas Oracle, which you can read for yourself. Mr. Masse is obviously working to overcome something, I am just not sure what. Perhaps you could inform us, Chris?


Enterprise prediction markets… the next big thing —not.

Opacity versus Openness

NEXT: Who did it?

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The truth about prediction markets

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Come to the wonderful world of collective intelligence, wisdom of crowds, and prediction markets!&#8230- The sun shines bright, the market-generated predictions are vastly superior to the polls as election predictors, and the track record of the public prediction markets stretches as far as the eye can see. There are opportunities aplenty in the field of prediction markets, and the trading technology is cheap. Every working enterprise can have its own internal prediction exchange, and inside every exchange, a set of enterprise prediction markets that correctly predicts the future of business, which their happy, all-American CEO listens to. Life is good in the magic world of prediction markets&#8230- it&#8217-s paradise on Earth.

Ha! ha! ha! ha!&#8230- That&#8217-s what they tell you, anyway&#8230- &#8212-because they are selling an image (just as Bernie Madoff did). They are selling it thru their vendor websites, vendor conferences, vendor-inspired articles in blogs, newspapers and magazines, and interviews of vendor data-fed professors in the media.

The prediction market technology is not a disruptive technology, and 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&#8217-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.

Here&#8217-s now our definition of prediction markets:

A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative represents the imputed perceived likelihood of the partially uncertain future outcome (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism &#8212-with or without an automated market maker.

Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future &#8212-anticipations that will be either confirmed or infirmed.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other meta predictive mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other meta predictive mechanisms. A highly accurate set of prediction markets has little value if some other meta predictive mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate predictions on its topic.

PS: I am updating a bit the content of this webpage, over time &#8212-so as to finesse the message.

Flu prediction markets can correct Google Flu Trends.

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2 practicing physicians laugh at using collective intelligence for nation-wide flu detection:

[…] Flu Trends tracks almost perfectly with data on influenzalike illnesses that the CDC obtains from doctors&#8217- offices. And as an added bonus, Flu Trends detects outbreaks up to two weeks earlier, when people are still sitting at home sneezing into their keyboards. […]

But if officials monitored only Flu Trends, it would be difficult to sort the signal from the noise —in addition to losing critical details on who is sick. Things besides an actual flu outbreak can cause people to search the Internet for flu information. We would imagine that Flu Trends would spike on the release date for a flu-related movie —maybe Outbreak 2: Electric Booga-Flu. And what happens if a pandemic flu scare hits the nightly news? Flu Trends&#8217- ability to detect when the real pandemic hits will be obliterated when people, including those without symptoms, start to search the Internet. Monitoring drugstore sales has the same issue: A jump in cold-medicine sales may mean a flu outbreak, but it could also mean that CVS is running a sale or that flu fear is causing people to stock their medicine cabinets. […]

They end their articles saying that Google can&#8217-t cure the flu, anyway. [???]

The response to the objections they jot down in the 2nd paragraph above is easy:

  • Informed by all other means, the event derivative traders can determine whether the spikes in Google Flu Trends are due to abnormalities (see the 2nd paragraph in the excerpt above) or due to the real spreading of influenza.
  • Hence, the flu prediction markets have a much higher social utility than Google Flu Trends. Chris Masse said so.
  • David Pennock, go writing another research paper about that.
  • History will retain that David Pennock was research scientist under Chris Masse&#8217-s reign in the field of prediction markets.

Google Flu Trends

Iowa Health Prediction Market

The “predict flu using search” study you didn’t hear about – by our good Doctor David Pennock


New York Times

WSJ Health blog

University College Cork (UCC) School of Medicine + Intrade

Dylan Evans&#8217- website

Previously: #1 + #2 + #3