Prediction Market Definition -now updated with the name of Chris Hibbert and Eric Cramptons cult leader built into.

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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 &#8212-i.e., the primary sources of information. (Garbage in, garbage out&#8230- Intelligence in, intelligence out&#8230-) Hence, prediction markets are meta forecasting tools.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism.

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.

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.

2008 US Presidential and Congressional Elections Prediction: The Sarah Palin effect has partially evaporated, but its remains point to a close race, come Tuesday, November 4, 2008.

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#1. Explainer On Prediction Markets

Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out&#8230- Intelligence in, intelligence out&#8230-

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 6 times out of 10, the favored outcome will occur- and 4 times out of 10, 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.

More Info:

– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts

– Prediction Market Science

– The Midas Oracle Explainers On Prediction Markets

– All The Midas Oracle Explainers On Prediction Markets

#2. Objective Probabilistic Predictions = Charts Of Prediction Markets

Put your mouse on your selected chart, right-click, and open the link in another browser tab to get directed to the prediction market page of your favorite exchange.

2008 US Elections

InTrade

2008 US Electoral College

2008 Electoral Map Prediction = InTrade – Electoral College Prediction Markets = Probabilistic predictions for the 2008 US presidential elections based on market data from InTrade = electoralmarkets.com

– This is a dynamic chart, which is up to date. Click on the image, and open the website in another browser tab to get the bigger version.

2008 US Elections Prediction: John McCain is now the favorite at InTrade, while all the other prediction exchanges still have Barack Obama ahead. Is InTrade quicker to incorporate the latest polls because of the bigger liquidity of its prediction markets?

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#1. Explainer On Prediction Markets

Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out&#8230- Intelligence in, intelligence out&#8230-

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 6 times out of 10, the favored outcome will occur- and 4 times out of 10, 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.

More Info:

– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts

– Prediction Market Science

– The Midas Oracle Explainers On Prediction Markets

– All The Midas Oracle Explainers On Prediction Markets

#2. Probabilistic Predictions = Charts Of Prediction Markets

Put your mouse on your selected chart, right-click, and open the link in another browser tab to get directed to the prediction market page of your favorite exchange.

2008 US Elections

InTrade

2008 US Electoral College

2008 Electoral Map Prediction = InTrade – Electoral College Prediction Markets = Probabilistic predictions for the 2008 US presidential elections based on market data from InTrade Ireland = electoralmarkets.com

– This is a dynamic chart, which is up to date. Click on the image, and open the website in another browser tab to get the bigger version.

2008 US ELECTORAL MAP PREDICTION: The 2008 US elections thru the prism of the prediction markets – 2008 US presidential and congressional elections – US President Prediction + US Congress Prediction – Barack Obama vs. John McCain

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#1. Explainer On Prediction Markets

Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out&#8230- Intelligence in, intelligence out&#8230-

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 6 times out of 10, the favored outcome will occur- and 4 times out of 10, 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.

More Info:

– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts

– Prediction Market Science

– The Midas Oracle Explainers On Prediction Markets

– All The Midas Oracle Explainers On Prediction Markets

#2. Probabilistic Predictions = Charts Of Prediction Markets

Put your mouse on your selected chart, right-click, and open the link in another browser tab to get directed to the prediction market page of your favorite exchange.

InTrade

2008 US Electoral College

2008 Electoral Map Prediction = InTrade – Electoral College Prediction Markets = Probabilistic predictions for the 2008 US presidential elections based on market data from InTrade Ireland = electoralmarkets.com

– This is a dynamic chart, which is up to date. Click on the image, and open the website in another browser tab to get the bigger version.

Prediction Markets for the 2008 Electoral College = US Electoral Map

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Interesting blog post from Lance Fortnow on the VP prediction markets. (I will soon blog about those.)

InTrade – Electoral Markets Map

Their brand-new widget:

Why the BetFair model is partially obsolete

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I like BetFair and the BetFair people very much. I was the only blogger to talk up the BetFair starting price system and the BetFair brand-new bet-matching logic. But the other face of the coin is that 2 aspects of their model are rotten to the core.

BetFair was created in 1999 and started off in 2000. Since that time, 2 major things arrived on the world scene. Number one, we have seen the emergence of the prediction market approach. Number two, the Web has taken our lives, and Google has become the dominant Internet search engine. Here are how these 2 major trends are affecting BetFair negatively.

  1. Decimal Odds (a.k.a. Digital Odds). – The prediction market approach means that we attack the public with the news and their associated probabilistic predictions, expressed in percentages, where high prices mean high probabilities of happening. BetFair, at the contrary, approach the public with a betting universe and an arcane vocabulary (&#8221-backing&#8221- and &#8220-laying&#8221-) where low prices mean high probabilities of happening. That is totally counter intuitive.
  2. Non-Indexable Prediction Market Webpages. – Like it or not, Google is now the world&#8217-s #1 media. We &#8220-google&#8221- anything, first thing in the morning. None of the BetFair prediction market webpages can be indexed by Google and the other Internet search engines. That means that BetFair is missing out, in my estimation, on hundreds of thousands of Google visitors each year. Those Google visitors will favor other prediction exchanges (e.g., HubDub) whose prediction market webpages are indexed naturally by the Internet search engines.

The British, who drive on the wrong side of the road, don&#8217-t have the 2 most important keys of the future.

US ELECTORAL MAP: Prediction Markets for the 2008 Electoral College

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ELECTORAL COLLEGE MARKETS: Probabilistic predictions for the 2008 US presidential elections based on market data from InTrade Ireland &#8212-(electoralmarkets.com).

By Lance Fortnow, David Pennock, and Yiling Chen. :-D

For more on probabilistic predictions, go to our &#8220-Predictions&#8221- page, or visit the prediction exchanges.

Alternatively, if you want an electoral map made of polls, go to electoral-vote.com.

The managing editor of CNBC.com asks readers whether they should report what the (play-money and real-money) prediction markets say. He is not that hot on the idea -to say the least. Which is why we should develop a blog network on prediction markets -to get rid of the journalists filter and report

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But the &#8220-gambling&#8221- nature puts some journalists off.

Is it just providing information &#8230- or promoting betting action?

See, that&#8217-s exactly why I want to develop my &#8220-Midas Oracle Project&#8221-.

Classic journalists and classic bloggers will never treat prediction markets with the maximum sophistication they deserve.

Only brand-new blog networks that will specialize in prediction markets will do a good job.

I&#8217-ll provide more details soon.

I hope that some of you will join this project. It should be a collective endeavor.

E-mail me to join.

Assessing Probabilistic Predictions 101

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Lance Fortnow:

[…] Notice that when we have a surprise victory in a primary, like Clinton in New Hampshire, much of the talk revolves on why the pundits, polls and prediction markets all &#8220-failed.&#8221- Meanwhile in sports when we see a surprise victory, like the New York Giants over Dallas and then again in Green Bay, the focus is on what the Giants did right and the Cowboys and Packers did wrong. Sports fans understand probabilities much better than political junkies—upsets happen occasionally, just as they should.

Previously: Defining Probability in Prediction Markets – by Panos Ipeirotis – 2008

[…] Interestingly enough, such failed predictions are absolutely necessary if we want to take the concept of prediction markets seriously. If the frontrunner in a prediction market was always the winner, then the markets would have been a seriously flawed mechanism. […]

Previously: Can prediction markets be right too often? – by David Pennock – 2006

[…] But this begs another question: didn’t TradeSports call too many states correctly? […] The bottom line is we need more data across many elections to truly test TradeSports’s accuracy and calibration. […] The truth is, I probably just got lucky, and it’s nearly impossible to say whether TradeSports underestimated or overestimated much of anything based on a single election. Such is part of the difficulty of evaluating probabilistic forecasts. […]

Previously: Evaluating probabilistic predictions – by David Pennock – 2006

[…] Their critiques reflect a clear misunderstanding of the nature of probabilistic predictions, as many others have pointed out. Their misunderstanding is perhaps not so surprising. Evaluating probabilistic predictions is a subtle and complex endeavor, and in fact there is no absolute right way to do it. This fact may pose a barrier for the average person to understand and trust (probabilistic) prediction market forecasts. […] In other words, for a predictor to be considered good it must pass the calibration test, but at the same time some very poor or useless predictors may also pass the calibration test. Often a stronger test is needed to truly evaluate the accuracy of probabilistic predictions. […]

Beware before citing the probabilistic predictions given by the prediction markets

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Steve Roman:

It’s good to see Intrade cited as authoritative but I don’t think the recession contracts have enough liquidity to accurately reflect the odds. Citing a contract price when there is only a small amount of liquidity is one issue the MSM does when the number may not be credible. Some others that come to mind:

1. Thinly traded contracts may not reflect true odds – For instance, the contract for the US entering a recession in 2008 is now trading at 31. A pundit may cite this as a 31% chance of the US entering a recession in 2008, but he would not note that there is a 10-point spread around that price, so that by trading one lot, the odds will change by 5 points up or down. It would be a meaningless move – or would it? In such a thin market it impossible to tell.

2. Contract rules are importantWill Larry Craig resign? Did a missile leave NK airspace? The contracts for these events were based on rules that could be interpreted to have the opposite meaning of what most people would assume they do.

Even with Intrade’s recession contracts the details are important. The contracts will pay off when there are two consecutive quarters of negative GDP growth. That’s easy to understand, but is only one definition of recession. In the US a recession starts when the NBER says it does, making it possible for the GDP definition and contract odds to show we are not in a recession as the NBER declares we are. Not a major issue, but one that should be disclosed.

3. Timeframe should be noted – US News is the latest violator of ignoring time frames when discussing price changes, http://www.usnews.com/blogs/capital-commerce/2007/10/16/recession-odds-continue-to-fall.html . When talking about price changes it is necessary to talk about the time period over which the changes occurred. Did the odds of a recession decline from 60% to 30% within the past week? The past month? Not citing a timeframe or including a chart means I have to go back to Intrade to check on my own.

Steve Roman&#8217-s blog: Nasty Brutish And Tall