Keith Jacks Gamble: simExchange is somewhat OK, but will remained confined in play-money land.

Keith Jacks Gamble on Brian Shiau:

Thanks for the response. Ita€™s interesting to see examples of product news stories and how your markets responded. These examples suggest that your game share prices are connected with sales. Ia€™m not surprised and Keynes wouldna€™t be either. His beauty contest view explains exactly why prices on the simExchange are connected to sales despite the fact that game shares have no intrinsic connection to sales (no dividends based on sales, nor the possibility to liquidate based on actual sales). The tradersa€™ comments you mentioned confirm that traders have picked up on this point and are buying and selling in anticipation of other tradersa€™ actions. Certainly, a lot of trading on Wall Street works the same way.

My point that game shares have no intrinsic value, unlike Wall Street shares, has two implications. First, ita€™s one reason that prices on the simExchange may deviate more from actual sales than prices on Wall Street exchanges deviate from actual value. Importantly, this statement doesna€™t say that simExchanges prices will deviate more, nor does it say that any deviation will be large. Further, your simExchange has at least one advantage for keeping prices near sales that Wall Street does not have: your market makers have infinite resources to keep prices at reasonable levels. Second, although irrelevant since the simExchange uses play money, the fact that game shares have no intrinsic value prevents the simExchange from ever working with real money.

Previous: Brian Shiau: The Sim Exchange Works Fine, Thanks.

Previous: Robin Hanson on the Sim Exchage + simExchange a Keynesian Beauty Contest &#8211- by Keith Jacks Gamble

Previous: The structure of simExchange game stocks

Previous: An invitation to join the simExchange beta + Since November 9, 2006, the Sim Exchange has attracted over 2,400 registered players. + Sim Exchange &#8211- How to earn additional money? + The Sim Exchange: Basic Trading vs. Advanced Trading + BetFair, Sim Exchange = Vertical Prediction Exchanges, First

The Giuliani manipulator buyer is back

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Judging from his hours, he&#8217-s based in the US.

We see you on the bid again, and your cosmetic offers as well. You are the whale in this market, but it&#8217-s a small pond. Be careful.

More details on this strange trading later&#8230-

Addendum:

Exhibit A: a view of trading known as &#8220-market profile&#8221- from March 1st through the 7th. Price is on the y-axis and volume is on the x-axis, instead of time. What typically develops on these charts are sideways normal-distribution-like patterns, which is unsurprising by the central limit theorem. Often, a jump to a new mean corresponds to an event. The pattern below is unheard of in liquid markets, except in risk-arb and other &#8220-peg&#8221–ish situations.

Giuliani Volume@Price 3/1/07-3/7/07

What first comes to mind is that the exchange is manufacturing volume with bogus &#8220-wash&#8221- trades, but the first time 33.3 printed (which is where half of the volume for March occurred as of yesterday), the price had been in the teens, and 33.3 marked an all-time high for the contract. This doesn&#8217-t make sense as fake volume nor some sort of internal initialization trade relating to TEN&#8217-s restructuring.

Yesterday&#8217-s trading suggests that a single buyer is pushing the market up and is currently successfully holding it at 40 while posting offers to appear as a passive market-maker. 1-2000 buy orders remained near 40 until about 10pm EST yesterday and returned this morning, EST. In these thin markets, this is quite a lot especially considering the high price level &#8212- and it is high since it&#8217-s almost a year before the first primary. Of course the recent buyer might be unrelated to whoever caused the anomaly at 33.3. To be continued..

Addendum:

After taking the weekend off, our buyer was back by 10am EDT this morning. He has to defend 33.3 which shouldn&#8217-t be too difficult considering that there are only 3 major candidates. Truth be told, 40 isn&#8217-t that high for this contract, and the price does more-or-less reflect recent polls, but this guy is awfully confident. There is a fine line between a manipulator and an overconfident trader who is too large for the market.

BoDogs Calvin Ayre Is Not In The Forbes 2007 List Of World Billionaires.

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And Forbes magazine has a streaming video posted on its website to explain why BoDog&#8217-s Calvin Ayre was listed in 2006, and why he was delisted this year. (Surprise, surprise: it has to do with the US executive government and the US Congress&#8217- crackdown on internet gambling and betting.)

– Forbes estimates that BoDog&#8217-s Calvin Ayre lost $500 million since last year. We pity him.

– BoDog&#8217-s Calvin Ayre has moved from Costa Rica to Antiga.

– BoDog&#8217-s Calvin Ayre will never come to the U.S. anymore.

Explainers on event derivatives (event futures), prediction markets (prognostic markets) and prediction exchanges (betting exchanges)

Explainers on event derivatives (event futures), prediction markets (prognostic markets) and prediction exchanges (betting exchanges) – at CFM

If you are a prediction market expert and have written and posted on the Web an explainer on prediction markets (an overview, a technical essay, or a wiki), feel free to contact me to give me its URL. I will be happy to list it there (and to plug it on Midas Oracle, maybe :) ).

Previous: Conditional and Combinatorial Betting – by Chris &#8220-Zocalo&#8221- Hibbert

External link: Implementing Hanson’s Market Maker – by David &#8220-Odd Head&#8221- Pennock

Psstt&#8230- If you actively maintain a webpage or a full website listing the prediction market resources, I&#8217-m a taker, too. :)

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

simExchange a Keynesian Beauty Contest

There&#8217-s an important difference between shares of ownership in real companies and these game shares. Shares of ownership in real companies have intrinsic value. Even for stocks that don&#8217-t pay dividends, shares of a real company represent ownership of the company&#8217-s assets. Thus, a stock&#8217-s price can&#8217-t fall too far below the company&#8217-s liquidation value because a smart trader could buyout the company and sell off its assets for more than the share price. Doing this makes money. I don&#8217-t think this property applies to the game shares since they don&#8217-t seem to be claims on anything but the ability to sell off the shares to someone else.

The simExchange seems like an excellent example of Keynes&#8217- beauty contest view of speculative markets. If there are naive traders who believe that shares have value based on actual game sales, then strategic traders will try to anticipate what naive traders will believe. Even though strategic traders know the shares have no intrinsic value (no dividends and no way to liquidate based on actual sales), they will trade to anticipate what naive traders will believe about sales. Thus, even though game shares have no intrinsic value (even in play money terms), as long as there is some level of belief that prices do correspond to sales, strategic traders will enforce this view.

I would be interested in a test of Shiau&#8217-s claim that &#8220-A stocka€™s price on the simExchange corresponds to the lifetime worldwide sales of a game, in which 1 DKP corresponds to 10,000 copies sold.&#8221- I could see this statement being basically correct if traders perceive that prices actually work this way and perceive that others perceive that prices actually work this way. Do the market makers try to enforce this connection? How do market makers on the exchange set their prices?

Previous: Robin Hanson on the Sim Exchage and The structure of simExchange game stocks

Robin Hanson on the Sim Exchange

Robin Hanson on the Sim Exchange:

Er, it sure sounds like they dona€™t enforce any connection at all at any date between the game mentioned by the asset and anything related to sales of that game. If there are not enough traders of good will to enforce such a connection, then with learning the connection will probably be lost.

Previous: The structure of simExchange game stocks

Previous: An invitation to join the simExchange beta + Since November 9, 2006, the Sim Exchange has attracted over 2,400 registered players. + Sim Exchange &#8211- How to earn additional money? + The Sim Exchange: Basic Trading vs. Advanced Trading + BetFair, Sim Exchange = Vertical Prediction Exchanges, First

Conditional and Combinatorial Betting

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After people have used Prediction Markets for a while and have gotten used to their ability to provide forecasts, they start thinking about different scenarios. Who would be the best Republican to face Clinton? How are the prospects for a market boom or crash effected by the winner of the election? How will poverty be affected by a proposed World Bank program? These kinds of questions can be posed in a number of ways using Prediction Markets. Markets can allow betting on conditional (if) or conjunctive (and) questions. Either one can be used to answer the what if questions, but they provide different choices to the bettors, and some make it easier for observers to decode the answers.

The easiest compound question to pose is a simple conjunction of two others. InTrade had separate markets in whether Bush would be reelected in 2004 (&#8221-BUSH&#8221-), and whether Osama bin Laden (&#8221-OSAMA&#8221-) would be captured before the election. Justin Wolfers and Eric Zitzewitz asked InTrade to add a single combined contract that would pay off if both came true. Their paper, Experimental Political Betting Markets and the 2004 Election shows how the prices on these three contracts can be combined to show how one event would be likely to effect the other.

InTrade created three separate claims to cover combinations of the two base questions. They were &#8220-Bush wins election&#8221- (BUSH), &#8220-Osama is captured before the election&#8221- (OSAMA), and the combination: BUSH&amp-OSAMA which would have paid out if both the others came true. Wolfers and Zitzewitz estimated the market&#8217-s conditional probability by comparing the price of OSAMA with the price of BUSH&amp-OSAMA. If the price levels were rational, the difference between the two prices had to equal the chance that Osama would be captured and Bush would not be reelected. Since the market price of BUSH&amp-OSAMA was 91% as high as the price of Osama, they concluded that that represented the conditional probability. A weakness of this conclusion is that while investors and arbitrageurs have an incentive to ensure that the price of BUSH is correct relative to ~BUSH, (and OSAMA with respect to ~OSAMA), there&#8217-s no bet that lets an arbitrageur exploit superior knowledge of the conditional probabilities.

Sometimes investors believe they know how one outcome will effect another, and want to bet directly on that linkage. If you were confident before the election that Osama&#8217-s capture would raise the probability of Bush&#8217-s reelection to 95% (above the level the the market prices implied), having the conjunctive bets didn&#8217-t provide a bet that would have looked beneficial to you. You might think you could buy Bush&amp-Osama (because you believe Bush&#8217-s chances are improved if Osama is captured) and sell ~Bush&amp-Osama (because this is the outcome your view says is least likely), but you&#8217-d lose both bets if Osama wasn&#8217-t captured (which is an outcome your prediction doesn&#8217-t specify.)

Conjunctive claims allow observers to deduce connections between claims, but since the investors aren&#8217-t directly rewarded based on the conditional probabilities, they have little incentive to ensure that the implicit conditional probabilities reflect their understanding of the connections between the outcomes. In order to evaluate different proposals we have to look at what investors would spend up-front, and then compare the possible outcomes and how the investor&#8217-s earnings change in each situation.

If Bush is a 60% favorite to be re-elected, and the market thinks there&#8217-s only a 10% chance Osama will be captured before the election, the odds on the conjunctions might be:

&nbsp-Bush reelectedBush defeated
Osama captured.09.009
Osama free.5.4

If you think Osama&#8217-s capture would improve Bush&#8217-s prospects to 95%, what should you buy or sell? Your prediction says that the ratio of Bush&amp-Osama to ~Bush&amp-Osama should be 19:1, but doesn&#8217-t have anything to say about Bush&amp-~Osama or ~Bush&amp-~Osama. If you buy Bush&amp-Osama and sell ~Bush&amp-Osama, you can make the prices match your beliefs better, but you&#8217-ll lose money if Osama isn&#8217-t captured. In order to support conditional bets directly, market operators have to find ways to allow traders to buy positions without exposing themselves to risks due to the independent cases.

A contract that acts like a conditional bet directly (written as BUSH|OSAMA, pronounced as &#8220-Bush given Osama&#8221- or &#8220-Bush conditional on Osama&#8221-) would pay off if Bush is elected, and return your investment if Osama bin Laden isn&#8217-t captured. That gives investors the right incentive.

&nbsp-Bush reelectedBush defeated
Osama capturedGain $1Lose investment
Osama freeReturn investmentReturn investment

In order to support betting on conditional probabilities, the bets have to be able to return the investors&#8217- money in particular cases. I know of three detailed proposals that have this property. They are: betting on arbitrary boolean expressions, representing the complete cross-product of possible outcomes (providing a complete set of Arrow-Debreu securities), and using the independent claim as currency for purchasing the dependent claim. There are two additional suggestions that might work, but haven&#8217-t been written down in sufficient detail to be sure.

Robin described and implemented Combinatorial Information Markets which represent probabilities and traders assets explicitly for all possible combinations of outcomes. Fortnow, Kilian, Pennock, and Wellman described how you might try to support bets on arbitrary boolean combinations of conditions. Their conclusion seemed to be that solving the general problem would be computationally infeasible. They didn&#8217-t describe how to address the problems they found, but I think it&#8217-s possible that a market that supported only binary combinations could be designed. And finally, Peter McCluskey built (and released as open source) USIFEX in 1999. It allows the user to use the coupons of the independent event as the currency. This combination allows traders to express conditionals directly. Unfortunately, that system didn&#8217-t attract a user base quickly enough, and Peter stopped development soon after the initial release.

For an article on Decision Markets written in 1999, Robin Hanson suggested creating markets using assets that pay off in &#8220-units of A if B passes&#8221- (and &#8220-&#8230- if B doesn&#8217-t pass.&#8221-), and allow traders to trade the assets for each other. The price of A|B in terms of B (which can be built from component assets) expresses the conditional bet. Robin didn&#8217-t explain how to set up a market in which people trade assets for assets and didn&#8217-t describe how to let the users see how various combination bets would express the conditional claims they might have been interested in. (This is the first of the two incomplete suggestions.)

Robin&#8217-s Combinatorial Information Market design uses a complex internal representation and can support arbitrary conditional bets. He built a prototype implementation that allows the user to explore these conditionals by choosing assumptions, and then adjusting probabilities in the resulting hypothetical situations. I wrote a prototype of my own in E. Neither prototype is more than a proof-of-concept that the institution works, and neither has been operated for any general market. The st
rength of this approach is that users can express conditional connections between arbitrary claims- this aspect has been shown to be effective in a laboratory experiment. Robin ran tests of this market after he proposed its use for PAM, and there were apparently no problems in running it with 6 traders estimating all outcome combinations for 8 events. The glaring weakness is that it doesn&#8217-t scale well. It&#8217-s not clear how to build a version that would work even with a market with dozens of questions and hundreds of users. I&#8217-ll describe this market in more detail in a future post in this series.

Peter McCluskey built USIFEX in 1999. It works quite differently and doesn&#8217-t seem to have the performance problems of the other proposals. The primary idea for supporting conditional trading is that you buy units of A|B using units of B as currency when betting on a conditional question. The effect is that when buying A|B, you end up with coupons of ~B as part of the purchase, and that&#8217-s what ensures you&#8217-ll be repaid if the independent event doesn&#8217-t occur. USIFEX is open source, but it hasn&#8217-t been maintained since it was released in 2000. The code was resurrected for use in the Swiss MarMix exchange, (AFAICT without making any use of the conditional betting features). The biggest weakness of Peter&#8217-s approach, as I recall, was that it would have taken a lot of users to ensure that the conditional markets weren&#8217-t extremely thin. A longer description of USIFEX is also in the works.

Todd Proebsting built an implementation of the Hanson design that works without conditionals. Dave Pennock wrote up a description of Todd&#8217-s approach, focused on the Market maker. I intend to describe the implications of Todd&#8217-s approach for betting on conditionals in a future post. (This is the second incomplete suggestion.) I think it might be straightforward to extend Todd&#8217-s approach to support conditional betting without running into the exponential growth of Robin&#8217-s solution. The drawback is that the market operator has to separately capitalize and enable every conditional question that you want the system to support, while Robin&#8217-s approach enables all of them by default. It&#8217-s also possible that Zocalo Open Source Prediction Market software would be compatible with this approach, where it&#8217-s clear that Zocalo would require substantial modification to support the Hanson proposal.

Other Articles in this series

  • PM intro: basic formats (2005-12-30)
  • PMs with Open-ended Prices (2006-01-05)
  • Looking at Both Sides (2006-04-17)
  • Book and Market Maker (2006-04-28)
  • Liquidity in N-Way claims (2006-07-19)
  • Continuous Outcomes using Bands and Ladders (2006-09-20)
  • Integrating Book Orders and Market Makers (2007-01-10)

Cross-posted from pancrit.org.

The structure of simExchange game stocks

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Brian Shiau (draft):

Contracts on most prediction markets are often binary contracts that pay depending on whether the event described by the contract occurs or does not occur. This structure is often referred as a binary option [1]. However, a prediction market is not restricted in solving yes or no questions. Contracts can be created to pay a scaling amount so that a prediction market can attempt to ascertain a quantity, such as how much a movie will gross in box office receipts.

Prediction markets have used contracts similar to futures to answer such questions. These contracts have some value that corresponds to a prediction and expire at a certain point, such as four weekends after a movie is released. At expiration, the contract holder cashes out the contract at the spot price (or the sum of box office receipts after four weekends) [2]. However, the problem with video games is that a game can continue to sell for years to come so any arbitrary expiration is not indicative of how well a game will sell. In creating a prediction market for video games, the simExchange required a structure that would accommodate the nature of the video game industry.

There are other quirks to the video game business. One particular problem that has been the ire of many analysts is the lack of comprehensive sales data [3]. Unlike Hollywood movies, video games do not have official sales figures every weekend. Instead, the industry relies on point-of-sale studies, surveys, and intelligent extrapolations from companies like NPD to get an estimate of how many copies a game has sold. The number of copies a game has sold will vary from source to source, although NPD is considered the standard by many in North America as it is the most comprehensive for North American sales.

Given these two problems, video games can continue to sell for years and the lack of data with absolute truth, the simExchange could not easily adopt the structure of most prediction markets already in existence. Instead, it sought a time-tested structure that has been used to answer a similarly mirky question: how much is a company that may last for decades really worth?

No one knows with absolute certainty how much a company is actually worth. That is one reason why the stock market exists for people to trade shares of a company. The stock market aggregates the information of all the traders to hopefully ascertain an accurate valuation for the company (this concept is known as the Efficient Market Hypothesis [4]). Due to the similarity of the issues, stocks on the simExchange function very similarly.

A stock&#8217-s price on the simExchange corresponds to the lifetime worldwide sales of a game, in which 1 DKP corresponds to 10,000 copies sold. These stock prices will climb or fall with monthly sales reports, just like a company&#8217-s stock price will climb or fall with quarterly earnings reports. A stock on the simExchange will also increase or decrease as a result of news on the product, just as a company&#8217-s stock will increase or decrease as a result of news on their products. If people believe a stock is underpriced given the data, people will bid it up and vice versa [5]. There is no automated function by the New York Stock Exchange to cash out a stock and pay shareholders a lump sum of cash depending on how the quarterly earnings for the company fared.

Eventually, a game will stop selling, just like eventually a company will stop growing. In this case the stock price will merely stagnate. Investors of game stocks can cash out just like they would with company stocks by selling their shares (or covering if they are short the stocks). The simExchange market makers will supply the liquidity to close those positions.

Due to this structure, in an efficient state where a diverse pool of traders are participating in the simExchange, game stock prices should become a strong predictor of the lifetime worldwide sales of video game titles [5].

References:
[1] Wolfers, Justin &amp- Zitzewitz, Eric. &#8220-Prediction Markets in Theory and Practice.&#8221- March 2006. (PDF)
[2] Hollywood Stock Exchange Frequently Asked Questions.
[3] Electronic Gaming Business, October 6, 2004.
[4] Shleifer, Andrei. Inefficient Markets: An Introduction to Behavioral Finance. New York: Oxford University Press, Inc. 2000.
[5] Chen, Kay-Yut &amp- Plott, Charles R. &#8220-Information Aggregation Mechanisms: Concept, Design, and Implementation for a Sales Forecasting Problem.&#8221- Hewlett Packard Laboratories and California Institute of Technology. March 2002.

Originally published on the Sim Exchange website. Republished on Midas Oracle .ORG with Brian Shiau&#8217-s permission. ((( Appreciated. :) )))

Related: Keith Jacks Gamble: simExchange is somewhat OK, but will remained confined in play-money land. + Brian Shiau: The Sim Exchange Works Fine, Thanks. + Robin Hanson on the Sim Exchage + simExchange a Keynesian Beauty Contest + The structure of simExchange game stocks + An invitation to join the simExchange beta + Since November 9, 2006, the Sim Exchange has attracted over 2,400 registered players. + Sim Exchange – How to earn additional money? + The Sim Exchange: Basic Trading vs. Advanced Trading + BetFair, Sim Exchange = Vertical Prediction Exchanges, First

BRIAN SHIAUS SIM EXCHANGE FEATURED TODAY IN THE FREAKONOMICS BLOG.

Freakonomics.

Previous: BetFair, Sim Exchange = Vertical Prediction Exchanges, First + The Sim Exchange: Basic Trading vs. Advanced Trading + Since November 9, 2006, the Sim Exchange has attracted over 2,400 registered players. + An invitation to join the simExchange beta

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