John Stewart unloads on CNBC… and Jim Cramer.

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The Daily Show With Jon StewartM – Th 11p / 10cCNBC Gives Financial Advice

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Video via Felix Salmon

The Daily Show With Jon StewartM – Th 11p / 10cJim Cramer Unedited Interview Pt. 1

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The Daily Show With Jon StewartM – Th 11p / 10cJim Cramer Unedited Interview Pt. 2

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The Daily Show With Jon StewartM – Th 11p / 10cJim Cramer Unedited Interview Pt. 3

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UPDATE: Jim Cramer on John Stewart

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

BBC

New York Times

WSJ Health blog

University College Cork (UCC) School of Medicine + Intrade

Dylan Evans&#8217- website

Previously: #1 + #2 + #3