Tag Archives: leading indicators

If Michael Giberson is wrong, then that means that Chris Masse is right.

Paul Hewitt: I dont’ know that you could say Chicago was the “weakest link”, just because it got dropped first in the voting. The political process caused it to go early. However, Michael Giberson is wrong to imply that the … Continue reading

Posted in All Best Posts Ever, Analysis (Accuracy & Precision), Analysis (Industry), Analysis (Meta), Collective Decision Making, Collective Forecasting, Collective Intelligence - Wisdom Of Crowds, Exchanges & Markets, Market Prices & Probabilities | Tagged , , , , , , , , , , , | 2 Comments

Who has the best analysis for Chicago’s failed bid for the Olympics?

Prof Michael Giberson: I think the “small, secretive committee” explanation is weak []. Bradbury does an excellent job sifting through the shifting coalitions revealed in the three rounds of IOC voting. Neither Madrid nor Toyko showed any significant ability to … Continue reading

Posted in All Best Posts Ever, Analysis (Accuracy & Precision), Analysis (Data), Collective Forecasting, Exchanges & Markets, Market Prices & Probabilities | Tagged , , , , , , , , , , , | 1 Comment

Why did all the prediction markets get the Olympic decision to reject Chicago so wrong?

The blogger at Sabernomics sees “this as a win for prediction markets, not a failure.” I don’t share his views, but I wanted to link to his piece for you to make up your own mind about the issue.

Posted in Analysis (Accuracy & Precision), Analysis (Meta), Collective Forecasting, Exchanges & Markets, Information Technology, Leading & Lagging Indicators | Tagged , , , , , , , , | Leave a comment

Never try to divine the IOC decisions on Olympics venues, Mike.

Prof Michael Giberson, No “careful observer knew this in advance” (about Chicago being a lemon), for the simple reason that if they knew, they would have downgraded Chicago on the InTrade and BetFair prediction markets, and Ben Shannon would have … Continue reading

Posted in Analysis (Accuracy & Precision), Collective Forecasting, Exchanges & Markets, Leading & Lagging Indicators, Market Prices & Probabilities | Tagged , , , , , , , , , , , | 7 Comments

Could we have divined that Chicago was a lemon?

Prof Michael Giberson: Chris, isn’t it odd for you to state “Chicago had not the slightest chance to begin with.” The phrase implies you believe that the probability of Chicago’s selection was near zero all along, but you have been … Continue reading

Posted in Analysis (Accuracy & Precision), Collective Forecasting, Exchanges & Markets, Leading & Lagging Indicators, Market Prices & Probabilities | Tagged , , , , , , , , | Leave a comment

Predicting the Present with Google Trends

Predicting the Present with Google Trends – (PDF file) – by Al Varian et al. Google Trends + Google Insights For Search Via Prof Levitt Previously: Flu predictions based on querying behavior (on Google and Yahoo!) are somewhat less impressive … Continue reading

Posted in Collective Intelligence - Wisdom Of Crowds, Forecasting (Science & Practice), The Internet | Tagged , , , , , , , , , , , , , | Leave a comment

Volume = (News Rate) * (Intrinsic Interest)

Sounds true to me. What do our research scientists think? Would you re-formulate it?

Posted in Analysis (Meta), Exchanges & Markets, Leading & Lagging Indicators | Tagged , , , , , | Leave a comment

Are the polls accurate? — Electoral college map prediction for the 2008 US presidential election

The United States presidential election of 2008 is scheduled for Tuesday, November 4, 2008. Here’s an aggregation of the state polls —it gives you a historical view of the potential electoral college (“270” is the magic number). – - As … Continue reading

Posted in All Best Posts Ever, All Guest Authors's Posts, Analysis (Data), Exchanges & Markets, Forecasting (Science & Practice), Leading & Lagging Indicators, Market Prices & Probabilities, Politics, Resources - References, The Global Economy | Tagged , , , , , , , , , , , , , | 3 Comments