Who is behind?

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IMPORTANT UPDATE REGARDING THE INCIDENT.

Somebody did set up a website making a fool of me. Searching who is behind this turned out the IP address of the NewsFutures server &#8212-but Emile Servan-Schreiber is as innocent as a lamb because this data was in fact fudged by the attacker (so as to wrongly put the blame on NewsFutures). It might well be the same thing for the IP that connected to comment here.

UPDATE:

Did the attacker try to pin it on, not just one, but *two* prediction market software vendors?

http://www.midasoracle.org/2009/03/13/did-the-attacker-try-to-pin-it-on-not-just-one-but-two-prediction-market-software-vendors/

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Niall is not happy…

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Niall O&#8217-Connor:

Cowardly bastards …if this can be confirmed I will pass the story on to one of my contacts at the Guardian. And I will ensure that the other cowards who received emails last Friday about the websites, but chose to keep quiet are also exposed- by informing their companies of this obscene example of corporate bullying.

How that prediction market consultant in Holland attracts economic advisers on the cheap

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Dear Mr. [PROFESSOR’S NAME GOES HERE],

I am writing on behalf of [PREDICTION MARKET SOFTWARE VENDOR’S NAME], a Netherlands based consulting firm, because our research has identified you as a scholar with some expertise in Prediction Markets or a related field. [THEY JUST SCRAPPED MIDAS ORACLE’S LISTINGS] We would like to assess your suitability and interest to join the panel of scientific advisors with [PREDICTION MARKET SOFTWARE VENDOR’S NAME] (www.url.com).

In doing so, we propose to explore your area of experience and knowledge of Prediction Markets. Having established this, we would like to list you as our scientific advisor on your area of expertise on Prediction Markets. This will allow us to seek your services for a negotiated fee, once your particular expertise in developing or interpreting a Prediction Market issue is required.

I trust this message clarifies in short the mutual benefits in our cooperation. Please feel free to contact me to discuss further details.

Sincerely,

[LOW-LEVEL EMPLOYEE’S NAME GOES HERE]
Communications Manager
[PREDICTION MARKET SOFTWARE VENDOR’S NAME]

Damped polls are superior to prediction markets as election predictors.

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Are Political Markets Really Superior to Polls as Election Predictors? – (PDF file) – by Chris Wlezien and Robert Erikson – 2007

Abstract

Election markets have been praised for their ability to forecast election outcomes, and to forecast better than trial-heat polls. This paper challenges that optimistic assessment of election markets, based on an analysis of Iowa Electronic Market (IEM) data from presidential elections between 1988 and 2004. We argue that it is inappropriate to naively compare market forecasts of an election outcome with exact poll results on the day prices are recorded, that is, market prices reflect forecasts of what will happen on Election Day whereas trial-heat polls register preferences on the day of the poll. We then show that when poll leads are properly discounted, poll-based forecasts outperform vote-share market prices. Moreover, we show that win-projections based on the polls dominate prices from winner-take-all markets. Traders in these markets generally see more uncertainty ahead in the campaign than the polling numbers warrant—in effect, they overestimate the role of election campaigns. Reasons for the performance of the IEM election markets are considered in concluding sections.

Conclusion

This paper has tested the claim that the Iowa Electronic Market offers superior predictions of election outcomes than the snapshots from public opinion polls. By our tests, the IEM election markets are not better than trial-heat polls for predicting elections. In fact, by a reasonable as opposed to naive reading of the polls, the polls dominate the markets as an election forecaster. This is true in the sense that a trader in the market can readily profit by “buying” candidates who, according to informed readings of the polls, are undervalued. Moreover, we find that market prices contain little information of value for forecasting beyond the information already available in the polls. Where then do the markets go wrong? To begin with, consider the vote-share market. The histories of market prices show that traders tend to hold persistent beliefs about the vote division that contradict the polls and that these persistent beliefs are often wrong. Incorrect beliefs get corrected only in the last days before the election, when the polls are difficult to ignore. The winner-take-all market tracks the vote-share market but compounds its errors by overvaluing long-shot candidates’ chances of victory, as if the market expects more campaign surprises than occur in reality. The existence of persistent mistakes in the vote-share market compounded by the degree of uncertainty about the vote-share estimates makes the winner-take-all market a particularly poor forecasting tool. Based on the experience of the IEM, if the polls show a candidate to hold a decisive lead but the market is unconvinced, bet on the polls. It should be noted that our daily poll projections are themselves rather crude instruments. Our robotic trading programs are informed by a flat prior, relying solely on the current polls and the days until the election but nothing more. Even when we compare market prices to the weekly average of poll-based forecasts, our instrument is primitive in that the week’s polls are not weighted for relative recency. But further perfection of our forecasting model from the polls would only advance our central argument. If we were to apply more rigorous modeling to obtain a properly weighted average of current polls and earlier polls, the victory of poll forecasts over the market forecast presumably would be more secure. One could argue that the results are drawn from a limited number of election years from a toy market with thin volume and limits on trader spending. With time, the IEM record could improve, and there is some suggestion that it has. Full-blown markets like Tradesports.com [or InTrade.com or BetFair.com] might in the end achieve an efficiency that so far has eluded the Iowa Electronic Market. Additionally, studies like the present one can suggest improved strategies to traders, which in turn improve the efficiency of election markets. Since our results are confined to a few runs of the toy Iowa market, some might claim a “so what” reaction. To such claimants, an important reminder is that the allegedly uncanny performance of the Iowa market has been touted as the primary evidence for the supposed superiority of election markets over the polls as an information source. The Iowa election market’s performance has not been so special after all. For now, our results suggest the need for much more caution and less naive cheerleading about election markets on the part of prediction market advocates.

Damped polls outperform prediction markets.

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Forecasting Principles:

Damping polls

Evidence from the literature shows that polls, in particular early in the campaign, are not reliable in predicting election outcomes but tend to overestimate the extent to which a candidate leads. To deal with these uncertainties, we added a damping factor to the RCP poll average. Damping is used to make forecasts more conservative in situations involving high uncertainty.

Our poll damping is based on research conducted by Campbell (1996) who showed that polls have to be discounted in order to achieve more reliable forecasts. Performing a regression analysis on historical poll data for the elections from 1948 to 2004, he derived a formula for discounting the polls according to their distance from Election Day. Campbell provided Polly the formula, along with a list of damping factors that vary by the number of days left before the election.

Currently, polls are discounted with a damping factor of ${factor}. Applying this factor, we calculate Polly&#8217-s discounted poll based forecast thus:

Polly&#8217-s poll based forecast = ((Latest RCP polling average – 50) * (1 – [damping factor])) + 50 = ((46.1 – 50) * (1 – 0.17)) + 50 = 46.8

Latest RCP polling average 46.1
Damping factor 0.17
Polly&#8217-s poll based forecast 46.8

Thus, our poll damping discounts a candidate&#8217-s lead in the two-party vote, depending on the days left prior to election. The further away the election day, the larger the damping.

Such damped polls have been shown to outperform sophisticated forecasting approaches like prediction markets. Comparing damped polls to forecasts of the Iowa Electronic Markets, Erikson and Wlezien (2008) showed that the damped polls outperformed both the winner-take-all and the vote-share markets.

Thanks to Andreas Graefe for the link.

Are Political Markets Really Superior to Polls as Election Predictors? – PDF file

For now, our results suggest the need for much more caution and less naive cheerleading about election markets on the part of prediction market advocates.

Previously: The truth about prediction markets

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).