Polls over prediction markets?

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&#8216-Are Political Markets Really Superior to Polls as Election Predictors&#8217- is a paper by Robert Erikson and Christopher Wlezian that calls into question whether prediction markets, and specifically IEM, is as accurate as proponents of prediction markets claim. The paper was highlighted here where it was suggested that advocates of prediction markets were turning a blind eye to it.

In the paper the authors show that while when you compare IEM with raw polls, IEM outperforms the polls however when you manipulate the poll data the polls are more accurate. The generate the manipulation the authors looked at poll data from elections from 1952 onwards which show that over time the early leader tends to lose that lead. They then used that relationship to manipulate polls for elections from 1988 onwards and compared the result with the IEM forecasts. The manipulated polls showed a higher level of forecast accuracy.

I think this is an interesting piece of research but it is a stretch to use this to claim that polls are more accurate than prediction markets. The fundamental problem is that when newspapers (or anyone else for that matter) quotes polls, they don&#8217-t refine them using historical data, they quote the actual poll result. If anything the authors have shown a small bias in IEM that one would now expect to get traded out (like the longshot/favorite bias in betting markets or the January effect in financial markets).

Fundamentally, the thing to note is that while polls make prediction markets more accurate, the converse does not hold.

Decision markets are markets where speculators set prices that estimate the consequences of a decision.

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&#8230- writes Robin Hanson (who is into prediction markets since the late 80s, and who is the smartest scholar on this topic).

I would call that &#8220-decision-aid markets&#8220-, then. And I would have the term &#8220-decision markets&#8221- define the strongest form of this tool, envisioned originally by Robin Hanson (PDF file) &#8212-that is, when the execution of the market-generated decision is compulsory.

LinkedIn vs. FaceBook prediction market

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Read and Write Web:

[…] However I am interested in prediction markets, so how about we define a specific prediction and then revisit it in six months? If Facebook and/or LinkedIn were public companies, we could test our predictive powers in the stock market with real money. However because they are private companies (for now), we can just do this for fun and bragging rights. Anyway public companies are now all boring, predictable enterprises- we have to recreate the fun in the private markets.

So the prediction, we think, from Stowe is this: “In 6 months Facebook will have more of your business contacts than LinkedIn”. We&#8217-ll check back in 6 months whether that prediction comes true. […]

Their poll shows that LinkedIn has the lead over FaceBook (this early Monday morning):

LinkedIn vs. FaceBook

Maybe PopSci PPX will be interested in floating a LinkedIn vs. FaceBook event derivative. I suspect that they would like to settle such an event derivative with objective, primary data &#8212-as opposed to an online poll.

UPDATE: Latest results of the poll&#8230-

LinkedIn vs. FaceBook

REMINDER: Midas Oracle is going to make an important announcement, soon.

Rod, how do you manage to publish math on your blog?

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Rod to me:

The math plug-in is more of a built-in feature:
http://wordpress.com/blog/2007/02/17/math-for-the-masses
http://faq.wordpress.com/2007/02/18/can-i-put-math-or-equations-in-my-posts

I did not install any plug-in. Since last February [2007], WordPress.com allows math typing in Latex. Midas Oracle should allow Latex typesetting without any plug-in. Just try to write $latex LaTeX$ in a post, and see if it works :-)

Midas Oracle runs WordPress.org (as opposed to being web-hosted by WordPress.com). I will have to search for a plugin.

External Link: Using Latex in WordPress – Sounds more complex than just installing a plugin&#8230- I&#8217-m investigating&#8230- Don&#8217-t hold your breath&#8230-

Bond prices on historical and contemporary civil war outcomes

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Bond prices on historical and contemporary civil war outcomes

Previous blog posts by Chris F. Masse:

  • Prediction Markets
  • Meet professor Justin Wolfers.
  • Become “friend” with me on Google E-Mail so as to share feed items with me within Google Reader.
  • Nigel Eccles’ flawed “vision” about HubDub shows that he hasn’t any.
  • How does InTrade deal with insider trading?
  • Modern Life
  • “The Beacon” is an excellent blog published by The Independent Institute.

Small comforts of prediction markets

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Yesterday I had dinner with a friend I hadn&#8217-t seen for a few years. I asked what he&#8217-d been doing, apart from being a nerd, and he said he&#8217-d been spending too much time following the U.S. presidential campaigns (actually just the Ron Paul campaign, but that&#8217-s not particularly relevant here). I realized that I don&#8217-t do this anymore. It could be because I&#8217-m maturing, but I&#8217-ll give credit to prediction markets.

Most of the yapping in the media is about the horse race and personalities, which I don&#8217-t care about, other than the status of the former. Instead I check prices at Intrade most days, which gives me a more accurate and much more concise status update than any amount of time spent reading or watching commentary.

Furthermore, betting that candidates I detest will win and against candidates I mind less, even in small amounts, really helps me not waste time thinking (mostly distressed thoughts) about the election.

So thank you prediction markets for the time and peace of mind!

IG Group buys HedgeStreet for $6,000,000.

Just as predicted by our Deep Throat in early October 2007 &#8212-&#8221-They are packaging HedgeStreet for a closing/fire-sale.&#8221-

RTT News.

U.S.-based sed HedgeStreet, which has operated the HedgeStreet Exchange, has liabilities of approximately $1 million and operating costs of approximately $325,000 per month. Currently, the company is not generating any revenue.

Hemscott:

IG Group chief executive, Time Howkins, said the acquisition gives the company the necessary regulatory approvals, technology, personnel needed to operate an exchange for US retail clients to trade in binary options. The company said it plans to re-launch the exchange around the end of its current financial year, after making some modifications, mainly the range of contracts offered.

IG Group:

Corporate Profile

IG Group Holdings plc offers speculative investment products to a retail and professional client base, through a number of well-known brands.

The group&#8217-s principal businesses give clients the ability to trade on financial markets. Our longest established business is financial spread betting, where we are the world&#8217-s leading provider (based on turnover), servicing a retail client base, primarily in the UK. Our rapidly growing Contracts For Difference and foreign exchange business services retail clients and market professionals around the world from offices located in the UK, Australia, Singapore and Germany. The group also offers spread betting on sports, entertainment and political events and binary betting on both financial and sports markets. More than 90% of the group&#8217-s client transactions are executed electronically.

2006-7 headlines

Revenue up 36% at ?122.0 million
EBITDA up 34% at ?70.4 million
– Strong EBITDA margin of 57.7%
– Diluted earnings per share up 33% at 14.52p
– Final dividend 6.5p per share- total dividend 8.5p per share
– EBITDA margin improvement from 54.5% in H1 to 60.3% in H2
– Successful launch of TradeSense in UK and recent launch in Australia
– Launch of PureDeal dealing platform
– Current trading is strong

The group&#8217-s business has grown rapidly since the late 1990s, with revenues having grown at a compound annual rate of roughly 40% over the past nine years. We have also developed IG Group into a significant multinational operation.

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Note: IG Group does not accept bets from customers based in the United States.


Author Profile&nbsp-Editor and Publisher of Midas Oracle .ORG .NET .COM &#8212- Chris Masse&#8217-s mugshot &#8212- Contact Chris Masse &#8212- Chris Masse&#8217-s LinkedIn profile &#8212- Chris Masse&#8217-s FaceBook profile &#8212- Chris Masse&#8217-s Google profile &#8212- Sophia-Antipolis, France, E.U. Read more from this author&#8230-


Read the previous blog posts by Chris. F. Masse:

  • Barack Obama is the 44th US president.
  • We already have prediction markets in future tax rates. It’s called the municipal bond yield curve.
  • DELEGATES AND SUPERDELEGATES ACCOUNTANCY
  • O’Reilly – Money-Tech Conference
  • Google Profiles
  • Event Derivative Exchange HedgeStreet is baaaaaaaaack… from the grave.
  • Sports Derivative Forum

Meet again James Surowiecki, author of The Wisdom Of Crowds.

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James Surowiecki

James Surowiecki, author of The Wisdom Of Crowds

Previously: James Surowiecki’s The Wisdom Of Crowds… still stands.

Previous blog posts by Chris F. Masse:

  • A second look at HedgeStreet’s comment to the CFTC about “event markets”
  • Since YooPick opened their door, Midas Oracle has been getting, daily, 2 or 3 dozens referrals from FaceBook.
  • US presidential hopeful John McCain hates the Midas Oracle bloggers.
  • If you have tried to contact Chris Masse thru the Midas Oracle Contact Form, I’m terribly sorry to inform you that your message was not delivered to the recipient.
  • THE CFTC’s SECRET AGENDA —UNVEILED.
  • “Over a ten-year period commencing on January 1, 2008, and ending on December 31, 2017, the S & P 500 will outperform a portfolio of funds of hedge funds, when performance is measured on a basis net of fees, costs and expenses.”
  • Meet professor Thomas W. Malone (on the right), from the MIT’s Center for Collective Intelligence.

James Surowieckis The Wisdom Of Crowds… still stands.

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James Surowiecki&#8217-s 4 comments at Overcoming Bias (in October 2007), responding to accusations that he got it all wrong about Francis Galton:

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James Surowiecki&#8217-s 1st comment:

&#8220-Galton did not even bother to calculate a mean, as he saw his data was clearly not normally distributed. He used the median (of 1207), which was much further off than the mean, but by modern standards clearly the better estimator. It was Karl Pearson in 1924 who calculated the mean.&#8221-

Robin [Hanson], before repeating falsehoods, you might want to go back to the original sources &#8212- or, in this case, to the footnotes to my book. Galton did, in fact, calculate the mean, long before Karl Pearson did. Galton&#8217-s calculation appeared in Nature, Vol. 35, No. 1952 (3/28/07), in a response to letters regarding his original article. One of the correspondents had gone ahead and calculated a mean from the data that Galton had provided in his original piece, and had come up with the number 1196. Galton writes, &#8220-he makes it [the mean] 1196 lb. . . . whereas it should have been 1197 lb.&#8221-

I find the fact that Levy and Peart wrote an entire article about Galton (and, to a lesser extent, about my use of him), and never went back and checked the original sources is astounding in its own right. (They actually wonder in the paper, &#8220-However the new estimate of location came to be part of Surowieki’s account,&#8221- as if the answer isn&#8217-t listed right there in the footnotes.) What makes it even more astounding, though, is that they&#8217-ve written an entire paper about the diffusion of errors by experts who &#8220-pass along false information (wittingly or unwittingly)&#8221- while passing along false information themselves.

It also seems bizarre that Levy and Peart caution, &#8220-The expectation of being careful seems to substitute for actually being careful,&#8221- and yet they were somehow unable to figure out how to spell &#8220-Surowiecki&#8221- correctly. The article is a parody of itself.

I&#8217-m happy to enter into a discussion of whether the median or the mean should be used in aggregating the wisdom of crowds. But whether Galton himself thought the mean or the median was better was and is irrelevant to the argument of my book. I was interested in the story of the ox-weighing competition because it captures, in a single example, just how powerful group judgments can be. Galton did calculate the mean. It was 1197 lbs., and it was 1 lb. away from the actual weight of the ox. The only &#8220-falsehood&#8221- being perpetrated here are the ones Levy and Peart are putting out there, and the ones that you uncritically reprinted.

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James Surowiecki&#8217-s 2nd comment:

Here are the links for the letter from Galton, where he reports the mean:

http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_1.htm
http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_2.htm

There&#8217-s no reason for debate here. Levy and Peart say &#8220-Pearson’s retelling of the ox judging tale apparently served as a starting point for the 2004 popular account of the modern economics of information aggregation, James Surowieki’s Wisdom of Crowds.&#8221- It wasn&#8217-t the starting point. The starting point was Galton&#8217-s own experiment, and his own reporting of the mean in &#8220-The Ballot Box.&#8221- Robin writes: &#8220-Galton did not even bother to calculate a mean.&#8221- He did calculate it, and he did report it. This fact shouldn&#8217-t be listed as an &#8220-addendum&#8221- to the original post. The original post should be rewritten completely &#8212- perhaps along the lines of &#8220-Surowiecki and Galton disagree about which estimate is a better representation of group judgment&#8221- rather than &#8220-Author Misreads Expert&#8221- &#8212- or else scrapped.

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James Surowiecki&#8217-s 3rd comment:

I appreciate Levy and Peart admitting their mistake. But they seem not to recognize that their mistake undermines the critique that&#8217-s at the center of their paper. Their paper, they write, is about the misconstruing of Galton&#8217-s experiment. &#8220-A key question,&#8221- they write, &#8220-is whether the tale was changed deliberately (falsified) or whether, not knowing the truth, the retold (and different) tale was passed on unwittingly.&#8221- But the account of Galton&#8217-s experiment was not changed deliberately and was not falsified. It was recounted accurately. Levy and Peart want to use my retelling of the Galton story as evidence of how &#8220-experts pass along false information (wittingly or unwittingly) [and] become part of a process by which errors are diffused.&#8221- But there&#8217-s no false information here, and no diffusion of errors, which rather demolishes their thesis. If they really want to write a paper about how &#8220-experts&#8221- pass along false information, they&#8217-d be better off using themselves as Exhibit A, and tell the story of how they managed to publish such incredibly shoddy work and have prominent economists uncritically link to it.

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James Surowiecki&#8217-s 4th comment:

To finish, Levy and Peart insist that their really important point still stands, which is that &#8220-When people quote Galton through Surowiecki, they tell Surowiecki&#8217-s tale, not Galton&#8217-s,&#8221- and that this is a problem because Galton&#8217-s thinking is being misrepresented. But as I said earlier, &#8220-The Wisdom of Crowds&#8221- was not intended to be a discussion of Francis Galton&#8217-s opinions on what&#8217-s the best method to capture group judgment, nor, as far as I know, has anyone who&#8217-s &#8220-Surowiecki&#8217-s tale&#8221- used the Galton example since used it to analyze Galton&#8217-s opinions. People aren&#8217-t quoting the Galton story because they&#8217-re interested in what Galton himself thought about the median vs. mean. They&#8217-re quoting it because they&#8217-re interested in the bigger idea, which is that group judgments (and this is true whether you use the median, the mean, or a method like parimutuel markets) are often exceptionally accurate. Levy and Peart have constructed a straw man &#8212- and, in this case, a straw man based on a falsehood &#8212- and then tried to knock it down.

Robin [Hanson] writes: &#8220-it is ironic that Galton made quite an effort to emphasize and prefer the median, in part because the data did not look like a bell curve, while your retelling focuses on him calculating a mean after checking for a bell curve.&#8221- What&#8217-s ironic about this? He did check for a bell curve, and he did calculate the mean. It&#8217-s the data themselves, not Galton&#8217-s interpretation of them, that I was writing about. (If he hadn&#8217-t calculated the mean, I would have happily told the story with the median, since it was also remarkably accurate, and demonstrated the same point about the wisdom of crowds.)

Finally, on the substantive question, Robin (and Levy and Peart) seem to think that because the distribution of guesses wasn&#8217-t normal, that makes using the mean a mistake. But this is precisely what&#8217-s so interesting: if the group is large enough, even if the distribution isn&#8217-t normal, the mean of a group&#8217-s guesses is nonetheless often exceptionally good.