Peter Schiff (November 13, 2009):
Peter Schiff (November 9, 2009) on US dollar carry trade:
http://en.wikipedia.org/wiki/Peter_Schiff
He is running for US Senate:
John Stossel (spot the intro where he says he loves InTrade):
Nate Silver’-s prediction (November 2, 2009): “-I’-d make Christie about the 4:3 favorite.”-
[ UPDATE: Nate Silver’s prediction post-mortem on the 2009 US elections.]
You can see that days before Elections 2009, InTrade was too heavy on Corzine:
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Our good friend Max Keiser (who appears in both the film and the teaser trailer) tells me that Alex Jones’-s channel on YouTube has had 4,592,178 views. Wow.
Buy John McCain at the end of 2007 (at around 5), sell high in 2008 —-and get rich quick. That is what Bethan and her husband (Jonathan) did.
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Today, InTrade CEO John Delaney is trying to milk out this get-rich-quick story (or a similar enough story). His message: You, too, can get rich quick…- —-what it takes is just registering your credit card with InTrade. 
What the InTrade CEO doesn’-t tell you is that luck was a factor in Bethan’-s sudden enrichment. Nothing wrong with tapping chance —-but honesty should have prompted John Delaney to mention it. And you will notice the absence of information for the x axis (the time). Marketing and honesty are 2 words that don’-t mix well in Ireland.
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ADDENDUM:
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Cato Handbook for Policymakers
Washington Post:
A soup-to-nuts agenda to reduce spending, kill programs, terminate whole agencies and dramatically restrict the power of the federal government.
Excellent.
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According to Alan Abramowitz, John Tierney has been “-greatly exaggerating the accuracy of the betting markets.”- “-They follow the polls. That’s it.”-
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My comment to Alan Abramowitz and John Tierney:
“-They follow the polls. That’s it.”-
Yes, they follow the polls. No, that’-s not it.
Traders also dig the news of the day and make anticipations about the outcome. For instance, towards the end of the 2008 Democratic primary, the polls and the mass media were still giving Hillary Clinton a very good standing, whereas the prediction markets (informed by a bunch of political experts who did the counting of the delegates and super-delegates) were telling us that she was as toasted as Lehman Brothers in the middle of the credit crunch crisis.
Are prediction markets useful? If John Tierney wants to answer this question, he should pick up a prediction market and put it in the social context of that day. Some prediction markets are more useful than others. In the case of the 2008 Democratic primary (a complicated matter), the prediction markets sided with the best informed political experts against the mass media and the polls. So to speak, they were an umpire. In that case, we see the emergence of a social utility. We now have the case for the media citing more the probabilities of the liquid (play-money and/or real-money) prediction markets.
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Previously: #1 – #2 – #3 – #4 – #5
External Link: Club of Growth
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PollTrack:
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I like the way they color this electoral college map —-with 5 colors only (simplicity is good). It is very clear and usable, I believe. You can see 6 states in gray (”-too close to call”-). I am heavily betting on Barack Obama for Florida and North Carolina. There will be a good payoff, next Tuesday —-maybe.
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Who will win Florida in the 2008 Presidential Election?
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Who will win North Carolina in the 2008 Presidential Election?
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Explainer On Prediction Markets
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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 can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). A 60% probability means that, in a series of events each with a 60% probability, then 60 times out of 100, the favored outcome will occur- and 40 times out of 100, the unfavored outcome will occur.
Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism —-with or without an automated market maker.
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. These event derivative traders feed on the primary indicators (i.e., the primary sources of information), like the polls, for instance. (Garbage in, garbage out…- Intelligence in, intelligence out…-) Armed with these bits of information, the speculators then trade based on their anticipations, which will be either confirmed or infirmed. Hence, the prediction markets (which are more than just an information aggregation mechanism) are a meta forecasting tool.
The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.
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More Info:
– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts
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More Charts Of Prediction Markets
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