Why the Hollywood Stock Exchange was sold to Cantor Fitzerald. – An insiders account.

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From the Horse&#8217-s mouth (Max Keiser):

Max Keiser is a financial engineer who likes to turn things into markets. After working on Wall Street during the eighties, Keiser turned his hand to Hollywood, where, rather than chase starlets as every other man in Hollywood was doing, he began commoditising those same starlets by trading them on the Hollywood Stock Exchange, a virtual market in celebrities that he created long before the BBC ripped his idea off with Celebdaq. The starlets loved him for turning them into the commodities they always wanted to be and Keiser was awarded three U.S. patents for the virtual specialist technology on which HSX runs. During his weekly NBC appearances on &#8216-Access Hollywood,&#8217- Keiser became the first person since the days of McCarthy to be boycotted by every major Hollywood studio at the same time. When Keiser accurately predicted weekend box office gross for nine weeks running on his HSX segment of NBC&#8217-s &#8216-Access Hollywood,&#8217- the major studios decided that free markets were not so great after all and called for NBC to remove the heretic in their monopolistic midst or lose access to Hollywood &#8216-talent.&#8217- HSX was sold to Cantor Fitzgerald and Keiser moved to Europe where he created Karmabanque, a virtual market in monetising dissent.

Addendum (November 16, 2006): I received this disambiguation note from someone who knows the HSX history&#8230-

Max Keiser was not involved with HSX at the time of the acquisition nor was he part of the process.

Addendum (February 23, 2007): Max Keiser replies&#8230-

To say that I was not involved with the sale of HSX to Cantor is incorrect. I did not endorse the sale of HSX to Cantor – I voted against it – because the deal with Cantor was not, in my opinion, above board.

TradeSports-InTrade: United Nations > John Bolton as US Ambassador to United Nations

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I&#8217-m curious to see who&#8217-s going to be on the &#8220-yes&#8221- side of this brand-new contract. From what I heard yesterday on NBC Nightly News, this neo-con is toasted. But maybe I don&#8217-t know the full story.

Addendum (November 15): Sacha Peter posted a comment&#8230-

Well, at least one person out there is currently willing to lay you 999:1 odds that he will get confirmed and he’s willing to stick his neck out to the tune of $10 against your $9,990 for it. It’s too bad even if you win you’ll still have to shell out $30 in commissions and $100 in expiration fees to collect your $10 in winnings. What a deal!

No change: Mispricing is greater in illiquid markets.

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Paul Tetlock’s latest paper on the subject of prediction markets “Does Liquidity Affect Securities Markets Efficiency?” follows the lines of the other authors whose model starts with the concept of first generation prediction markets, designed in such a way that their prices express probabilities.

First: We should not be surprised that those markets “underprice high probability events and overprice low probability events”. This is a consequence of continuous information arrival. Any binary option MUST show this behaviour, mathematically, depending on its In-the-money or Out-of-the money state.

In the framework of Price Information Theory, with continuous information arrival, you “lose” probability until the prediction horizon sigma sqrt T of the price differential. No “irrationality” there. (Remember: “Austrians” start on the premise that man is rational.)

Second: The immediate analogy from such binary contracts to behaviour of securities markets is not permissible. Securities markets price discounted future cash-flows in consideration of the two risks (ex-ante volatility and noise) affecting them. Applying the problematic binary framework to securities prices does not make binary options a security, they stay what they are. (Price predictions on rice in China does not make them edible.)

Third: Based on this, it is easy to explain why the conclusions of the paper appear overdrawn: The better the probability of a binary follows the information decay, the more mispricing the presented model would detect. Mr. Tetlock final thoughts appear to run in a similar vein by stating in the end that “…, liquidity may only appear to be a priced risk factor because it captures some systematic element of mispricing.”

So: On this one, let’s stay with the cited conventional models (Kyle) plus some empirical evidence from “real” securities markets: Mispricing is greater in illiquid markets.

Hubertus Hofkirchner

Chris, I need an internship or job in the prediction market industry, this summer.

My answer to him/her:

Don&#8217-t give the first fig about the prediction market industry.

Go working at an exchange, preferably in Chicago, and learn everything you can about markets.

In 10 years, all the Chicago exchanges will float event derivatives.

Good luck,

Signed: Chris Masse

External Links:

To get all the links to the exchanges, visit the &#8220-Links&#8221- page on this blog (which David Pennock is so jealous of), or visit the &#8220-Exchanges&#8221- webpage at CFM.

That is all, folks. Read the previous blog posts by Chris. F. Masse:

Nominatibility and Electability – 2008 presidential prediction markets

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Via our usual suspect Mike Linksvayer (recently featured in the New York Times for his weird diet), David Schneider-Joseph (a Foresight Exchange fanboy) on how to measure real electability of the US presidential candidates. Go reading his reasoning. His conclusion:

Put this way, it&#8217-s not a surprise that candidates with greater party ties have a greater chance of being nominated than their electability deserves. But that&#8217-s not the same thing as saying that their electability is actually lower than that of their competition.

The five minutes on my 15 minutes of WSJ fame.

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Coming from a politics-obsessed family, we (family and I) have been fans of predicting election outcomes for as long as I can remember. We are all conservative-libertarians of one hue or another, and I began writing &#8220-wingnut&#8221- screeds in eighth grade for my junior-high newspaper. What with the Florida Bush recount and 9/11, a superpoliticized era had dawned. My first forecast was 2002, and I got all the Senate races right but for one. Uncanny, I thought. Then came 2004, and I nailed that one too. Really uncanny&#8211-but then again, every clock was right twice a day, and this being the high and higher tide of &#8220-my side,&#8221- my predictions didn&#8217-t seem so uncanny in retrospect.

Fast forward to October 2006, and I was a junior in college with a mediocre academic record in finance and Chinese. An election was gearing up. I wanted to put my forecasting ability to the test. I also realized that, by blogging the rationales for my trades, it could become a valuable tool in my quest for a summer internship/job, to represent a side of me that my GPA didn&#8217-t represent at all. Not exactly lacking confidence, I put $2500 where my mouth was, and soon afterwards plowed in another $1000. I shifted in and out of many positions, but the common denominator was (as I said on my own blog some days ago) that I believed the market was underestimating the intercorrelation between congressional races, and especially Senate races all over the country. In other words, I bet very heavily on the Democrats taking both houses.

Three or so weeks into my blog, I was getting scattered, but very positive feedback about my material. People in Tradesports threads began quoting it, and a major Tradesports speculator asked me for some further opinions regarding the direction of the 2008 US presidential nominations markets. (I told him not to do anything other than short Hillary, but to especially not short Barack Obama, until after the election, and I couldn&#8217-t have any &#8220-gut feeling&#8221- until I had gauged what a Dem election victory would mean.) So I knew my material was good, but I was still pretty surprised, not to mention ecstatic, when WSJ reporter Jim Browning contacted me for information about election prediction markets. So I happily gave him everything he asked, and the superb WSJ article was the result. (That&#8217-s the non-$$, Pittsburgh P-G version.) But as our conversations continued into election night, I begain to despair about my positions&#8230-

In Virginia, George Allen had about a 12,000-vote lead with about fifteen counties remaining to vote. I knew they were in the pro-Webb counties (Fairfax, Loudoun, Richmond City&#8230-) but those precincts ranged from barely better than even to 72-28 (Richmond). Webb would have required statistically&#8230-.unlikely turnout and/or margins in order to win. A lot of people on DailyKos and other communities emotionally invested in a Webb victory, processing new updates literally seconds after they came, had given up on Webb. Harry Reid came on TV and his body language screamed, &#8220-I don&#8217-t think the Senate is in play anymore, even though I thought it was a couple of hours ago&#8230-but that was too much to ask, anyway.&#8221- Without Virginia, the calculations for the Democrats&#8217- taking the Senate became very grim, very fast.

Final polls (which I had spent the previous weekend trashing) showed VA breaking for Webb, comporting well with my own intuition. As the returns came in, however, Allen seemed to have an insurmountable lead with about 96% of precints reported. I concluded that Allen would win re-election, barely. Michael Barone&#8217-s forecast to the contrary, I noticed that the remaining precincts to report were healthy-majority Democrat (about 60-40, 65-35), but I didn&#8217-t think that Webb would be able to cut Allen&#8217-s lead in half&#8211-well, maybe half, but not zero it out. (I learned only later that when Virginia says &#8220-precincts reporting,&#8221- it apparently does not include absentee ballots when it says that. Or it reported them before it started tallying up the actual votes from the voting booths on that day. Or something. But a bunch of absentee ballots flowed into Fairfax later that netted about 7k more votes for Webb.)
However, rewinding to that despairing moment, the Democratic machines in Richmond City, Fairfax and Loudoun had waited until all other precincts had reported before reporting. Now, I don&#8217-t know about Virginia, but I know that in Missouri, the urban Democratic machines in STL and KC have a certain notoriety (in some circles, anyway) of waiting until every other precint has reported, and then releasing surprisingly high results (that usually imply incredible voter turnout&#8211-certain STL precincts reporting 97%, 100+% turnout isn&#8217-t unheard of), magically pushing the Democratic candidate over the top by a fraction of a percentage point. (I don&#8217-t want to start a flame war here&#8211-I think American politics is a blood sport, both sides have their different ways of playing dirty, and this was just something I didn&#8217-t factor in.) And six to twelve months after the election, some low level Democrats get a year in jail for voting fraud. It happens like clockwork, except that this time around I don&#8217-t think the MO Dems will need to resort to that. But I digress&#8230-

So I figured VA was lost when it wasn&#8217-t, and I puked up all the SENATE.GOP shorts. At one point, over 50% of my entire principal was gone. Then, after despairing for about ten minutes, I went back to the TS markets intending to try and make back what I could. Then I realized that Webb had magically jumped into a 2200 vote lead in VA with 100% of precincts counted. I had already looked at the counties and their turnout/margin statistics and figured that couldn&#8217-t have happened, but it had. So after losing over a couple grand&#8230-not to mention feeling like a complete idiot for throwing away $8000 by buckling at the last possible second, I hopped back on the SENATE.GOP train and rode it down to zero, and made back that entire original investment, plus about $150 left over.

So a lot of lost hair, Wheat Thins, NoDoz, bad grades and exhaustive political analysis later, I felt pretty vindicated, even though I had managed to squander 90% of the potential compensation. (I did indeed lose hair.) I had staked 1,000 shorts against SENATE.GOP.2006, well against the majority view of the market. As I recall, total volume going into the election was 35k or 40k trades, but because some significant fraction of that was the same positions being flipped back and forth between a stagnant pool of traders before I&#8217-d arrived, it was probably closer to 5% of outstanding positions. If my money hadn&#8217-t buttressed the market-minority&#8217-s view, the price would have been even more inaccurate&#8211-before election day, the price hovered around 70 percent, and without my heavy position on the &#8220-minority&#8221- side, it would have been closer to 80-20 in favor of the GOP holding onto the Senate. Plus, going into the election, I had stuck by my calculations even as the market had continued to erode my investment. Having that kind of confidence and analytical precision vindicated meant much more to me than $8-9000 in potential winnings lost.

&#8211-Alex Forshaw

P.S. On that non-mercenary note, I&#8217-m seeking an internship this summer involving event derivatives trading/research or options trading, either academia- or finance-based. If you&#8217-re interested, please e-mail to: [email protected]

What happens if you did an opinion poll, but instead of asking each individual how they intended to vote, you asked each individual what they thought the outcome of the election would be?

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Felix Salmon (from the RGE Monitor):

The really irrational thing would seem to be why we still place so much faith in opinion polls. Opinion opinion polls would be much more accurate.

Prediction Market Forum:

Global Imbalances – (Start of the Thread = &#8220-DISCUSSION&#8221-) — NewsFutures and RGE Monitor

SCIENTIST DAVE PENNOCK IS LAUGHING ALL THE WAY TO HIS NEW YORK BANK.

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&#8230- Psstt&#8230- TradeSports traders&#8230- Wanna be rich?&#8230- Do like David Pennock: Get a PhD&#8230- with a major in probabilities&#8230-

Although TradeSports’s individual state predictions and overall Senate prediction were entirely consistent, one might argue that traders underestimated the degree of dependence (correlation) among states’ elections. In fact, I made a few bucks selling the “GOP Senate control” contract on TradeSports using exactly that reasoning. 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.

Speculating (and hedging?) on US presidential prediction markets would have social utility. Dixit Robin Hanson.

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If Deep Throat is right and the CFTC has indeed already given its stamp of approval to presidential prediction markets, then HedgeStreet and USFE would be well advised to listen to professor Robin Hanson&#8217-s idea with great attention:

Using data from a site like Tradesports.com to forecast who will win an election is just scratching the surface, said Robin Hanson, associate professor of economics at George Mason University in Fairfax, VA, and one of the founders of the field of prediction markets. Although the economic incentive is high for picking a winner, Hanson would like to see prediction markets forecast the consequences of a candidate getting into office. Will unemployment go up or down? Will we have more or less trouble in Iraq? Will we decrease or increase the deficit? &#8220-The social value of telling people who&#8217-s likely to win is questionable. The social value of telling people the consequences is arguably far higher,&#8221- said Hanson.

My Question To Professor Robin Hanson: The prediction market that would be interesting would be the one featuring the elected candidate (the so-called &#8220-President-Elect&#8221-). But the expiry of the other prediction markets, featuring the defeated presidential candidates, would be impossible to judge, since these presidential candidates by definition won&#8217-t take office and have any power on the US government. And if the game is murky, you won&#8217-t find any traders willing to risk his/her shirt on those kinds of US presidential prediction markets.

Addendum: Robin Hanson has posted a comment, and I republish it here for everyone to see&#8230-

Let U = the unemployment rate, D = Democrats win, and R = Republicans win. An exchange rate between “Pays $U if D” and “Pays $1 if D” gives an estimate of E[U|D]. Similarly, an exchange rate between “Pays $U if R” and “Pays $1 if R” gives an estimate of E[U|R]. We can compare E[U|D] and E[U|R] to see which candidate is expected to have a lower unemployment rate. And we know how to pay off all of these assets, no matter what happens.

Robin Hanson would like to see prediction markets forecast the consequences of a candidate getting into office. – REDUX

The TradeSportss NKM scandal vs. the BetFairs 2006-Senate case

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JC Kommer was prompt to comment on my 2006-Senate piece:

Double standard Mr Masse.
Betfair is doing exactly the same thing that Tradesports in the NKM “scandal”, going for the literal reading of the rules as they should.

My Answer To JC Kommer:

I disagree.

NKM Scandal: TradeSports made two grave errors. Number one, they engraved in marble that they would rely ON A SINGLE SOURCE OF INFORMATION (the US DOD) for the expiry of the contract. This is totally crazy. The truth should be established using as many reliable sources as possible or appropriate (including second-hand but reliable sources like the White House, which is fed by the DOD on military issues). What matters is the truth, gathered from multiple sources, not one particular source that could have an irrational or secretive behavior at some specific times. Number two, while establishing this one-single-source-for-expiry contract, TradeSports was not aware of the well known and public fact that the US DOD never issues detailed statements on North Korea matters. Information about North Korea is &#8220-classified&#8221-. Logically, the US DOD did not confirm directly and in a very formal way that North Korea fired missiles. (Note that a case can be made that the US DOD did indeed confirm the North Korea firing of missiles, directly and in an elliptic way, which many observers found it satisfying enough for expiry purpose). So, in my view, as I have described above, TradeSports made two grave errors. They apologized to their traders, but they did not take action to compensate the victims of their two errors. The victims here are the &#8220-yes&#8221- speculators on the NKM prediction market. They were correct in their prediction, but they lost their shirt in the end. Note that the &#8220-yes&#8221- bettors and virtual speculators at BoDog and NewsFutures were justly gratified for their accurate prediction on the NKM topic. Which shows once again that the problems originated from TradeSports, and not from the &#8220-yes&#8221- speculators. TEN CEO John Delaney (managing TradeSports) should have compensated the victims. Instead of that, the first action he took on the Monday when the scandal broke was to retaliate against Chris Masse, who gave airtime to the screwed-up &#8220-yes&#8221- speculators.

2006-Senate Case: There are no &#8220-victims&#8221- here, since BetFair sticks with the ORIGINAL contract &#8212-as CLEARLY written ON DAY ONE on their &#8220-RULES&#8221- tab, and as understood correctly by everybody who can read plain English. NO SURPRISE, NO CONTROVERSY. “Which of these parties will have MORE SEATS in the US Senate following the 2006 US Senate Elections?” is a very different question than &#8220-Which of these parties will CONTROL the US Senate?&#8220-. There is no ambiguity in the first question. In the second question, it&#8217-s understood that you could control the US Senate with your allies (the Independents).