Tag Archives: Robin Hanson

Marginal Revolutions Tyler Cowen re-writes history to favor his GMU colleague.

Posted on by
2

No Gravatar

I respectfully disagree with that.

#1. BetFair floated CEO Resignation event derivatives back in 2004 &#8212-2 years before Robin Hanson&#8217-s CEO Firing idea [CORRECTION: see below], and 3 years before PaddyPower&#8217-s press release.

#2. Robin Hanson was about decision markets, in his Forbes Op-Ed &#8212-neither about prediction markets nor book betting.

#3. The main obstacle of implementing Robin Hanson&#8217-s concept of decision markets is the business executives&#8217- egos. Why would they outsource the decision making to a crowd machine if the added value is marginal? Publishing complacent blog posts on the premier economics blog won&#8217-t solve this problem.

Trying to sell decision markets to business executives is like trying to sell robotized dildos to young, horny men. Whatever the merit of the product, they don&#8217-t need it &#8212-they prefer using their own thing (if you see what I mean). :-D

&#8212-

UPDATE: Comment from Robin Hanson&#8230-

You make a valid point about there being a difference between CEO futures and decision markets. It is the board, not the CEO, who we might hope would be willing to overrule the CEO ego. And I&#8217-ve had a web page arguing for CEO decision markets since 1996.

&#8212-

Robin Hanson (back in April 1996):

[…] The main proponent of this Vote No campaign thinks the following proposal of mine has promise. I propose to create, for each stock, a separate market in that stock for trades which are &#8220-called-off&#8221- if the CEO does not step down in the next year. The price of the stock in this market should indicate the market&#8217-s expectation of the value of that company with a different CEO. If that stock price is consistently and significantly higher than the ordinary stock price, that should be a clear market signal, from informed traders, for the CEO to step down. (If there is no price, because there is no trading, then there is no signal.)Ordinarily CEOs respond to statistics showing how poorly their company is fairing relative to similar companies by explaining how they are really different. And they respond to statistics of unhappy shareholders by pointing out how little incentives any one of them has to become well informed. These excuses should be blunted by my proposal, and board members may more plausibly fear legal action for ignoring these market signals.

This proposal is an example of a more general concept of policy markets.

What should be learned from the Overcoming Bias fiasco?

Posted on by
Reply

#1. That mistake could happen to any blogger (including moi), as we are all keen to re-publish and link to other people&#8217-s writings without checking and researching the foundations of their rationale.

#2. James Surowiecki taught a lesson in journalism to Robin Hanson.

#3. Robin Hanson should have published James Surowiecki&#8217-s letters to the editor as a new blog post &#8212-in addition to posting addenda to the original, flawed, misleading blog post.

#4. James Surowiecki has confirmed that he has the capacity and the legitimity to lead the field of prediction markets. [Of course, Robin Hanson is capable of mutant abstractions (MSR) whereas James Surowiecki is not.]

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

Separating cheap talk from truly held beliefs

Posted on by
2

No Gravatar

Plight of the Fortune Tellers: Why We Need to Manage Financial Risk Differently

&#8212-

In his book, Plight of the Fortune Tellers, Riccardo Rebonato describes how an invitation to bet can be used to separate cheap talk from truly held beliefs (and, in the process, ruin an otherwise engaging dinner conversation).

In the early to mid 1990s in the United Kingdom and in other European countries a widespread fear developed that a variant form of CJD might spread to humans. CJD is a fatal illness—also know as “mad cow disease”—that is well-known to affect bovines. The variant form was thought to have contaminated human beings via the ingestion of beef from cattle affected by the disease. … When the first human cases appeared scientists did not know whether they were observing the tip of an iceberg or whether the relatively few observed cases, tragic as they were, constituted a rather limited and circumscribed occurrence. “Expert scientists” were soon willing to go on record with statements to the effect that “it could not be excluded” that a catastrophe was unfolding. The nonscientific press was all too eager to jump on the bandwagon, and extravagant claims were soon presented, such as that hundreds of thousands, or perhaps even millions, of lives could be lost over the next decade. Specific probabilities were not stated, but the prominence of the reporting only made sense if the possibility of this catastrophic event was nonnegligible: the newspapers, at least judging by the inches of column space devoted to the topic, were not talking about a risk as remote as being hit by a meteorite.

As the months went by … the number of cases did not significantly increase…. Looking at the data available at the time with a statistical eye, I was becoming increasingly convinced that the magnitude of the potential effect was being greatly exaggerated. At just the same time, a well-educated, but nonscientist, friend of mine (a university lecturer) was visiting London and we decided to meet for dinner. As the conversation moved from one topic to another, he expressed a strong belief, formed by reading the nonscientific press, that the spread of CJD would be a major catastrophe for the U.K. population in the next five to ten years. He was convinced, he claimed, that “hundreds of thousands of people” would succumb to the disease. … I challenged him to enter a bet, to be settled in ten years’ time, that the number of occurrences would not be consistent with a major epidemic. My friend refused to take me up on my offer, despite my very attractive odds (attractive, that is, given his stated subjective probabilities). He claimed that “one does not bet on these things”- that he found my proposal distasteful- that, anyhow, he was not a betting man- and so on. I explained that I was not trying to gain material advantage from a possible human disaster, but I was simply probing the strength of his convictions on the matter. Ultimately, the bet was not entered, and the evening was rather spoiled by my proposal.

Julian Simon’s bet with Paul Erhlich is perhaps the most famous example of the use of a bet to test the strength of convictions. Robin Hanson has done a substantial amount of work on the foundations of such &#8220-Idea Futures&#8221- mechanisms. A similar concept underlies Long Bets and the Simon Exchange.

At Long Bets they say, “Long Bets is about taking personal responsibility for ideas and opinions.” That is the basic idea I had in mine when I suggested that “it would be a real public service to run well-conceived prediction markets based on the grandiose political pronouncements of the ‘chattering classes’.” It is all about an author taking personal responsibility for the opinions he publishes by, in effect via the prediction market, offering to fund countering opinions on well-defined claims if and only if those countering opinions turn out to be true.

(See also Chris Masse’s post. I’m not claiming any originality on my part here, I’m just trying to nudge the idea closer to common practice by suggesting a potentially interesting and fruitful area of application.)

Naomi Klein? Ann Coulter? Pat Buchanan? Michael Moore? Maybe they believe what they write, and would be willing to subsidize a prediction market out of their book royalties to demonstrate the strength of their convictions. Or how about the books from the current crop of U.S. presidential candidates—I wonder if these books contain any claims that are specific and substantive enough to be either true or false.

If such punditry-based prediction markets were common, mistaken-but-honest demagogues (those pundits who actually believe what they write, and are willing to stand behind it) would end up subsidizing more thoughtful analysts participating in the markets- correct honest demagogues would end up taking home larger financial rewards- and dishonest demagogues would dissemble, seek to avoid being pinned down on specific claims, and when pressed for actionable claims they would run and hide.

[Cross posted at Knowledge Problem.]

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

Posted on by
Reply

No Gravatar

&#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.

HISTORY: Prediction Markets Timeline

Posted on by
16

For an updated version of this document, see the &#8220-paged&#8221- Prediction Markets Timeline.

–

CHRONOLOGY &amp- HISTORY: Prediction Markets Timeline

–

Feel free to post a comment or contact me, and I&#8217-ll correct or add a factoid. Thanks.

–

#1. Historical Prediction Markets

According to Paul Rhode and Koleman Strumpf, prediction markets almost never got it wrong forecasting the 19 presidential elections that took place from 1868 to 1940. (PDF)

#2. The three Iowa Electronic Markets founders (Robert Forsythe, Forrest Nelson and George Neumann)

&#8220-We ran our first market in 1988. We didn’t have regulatory approval at that point so we were restricted solely to the University of Iowa community. We had under 200 traders and under $5,000.&#8221- &#8211- [Robert Forsythe – PDF file]

– [CFTC’s no-action letter to the IEM – 1992 – PDF file]

– [CFTC’s no-action letter to the IEM – 1993 – PDF file]

#3. Robin Hanson

a) Robin Hanson set up and ran a rudimentary prediction exchange (a market board, PPT file) in January 24, 1989. The outcome to predict was the name of the winner of a Poker party.

b) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange &#8212-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.

Robin Hanson: &#8220-I started a market at Xanadu on cold fusion in April 1989. In May 1990, I started a market there on whether their product would be delivered before Deng died.&#8221-

c) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a bunch of imagination-based prediction markets. See the Murder Mystery Evening described by Barney Pell &#8212-circa June 8, 1989.

d) Until evidence of the contrary, it seems that Robin Hanson was the first to write a paper on prediction markets created and existing primarily because of the information in their prices (as opposed to markets created primarily for speculation and hedging).

Could Gambling Save Science? &#8211- (Reply to Comments) &#8211- by Robin Hanson &#8211- 1990-07-00
Market-Based Foresight: a Proposal &#8211- by Robin Hanson &#8211- 1990-10-30
Idea Futures: Encouraging an Honest Consensus &#8211- (PDF) &#8211- by Robin Hanson &#8211- 1992-11-00

e) Robin Hanson godfathered the Foresight Exchange (created in 1994) and NewsFutures (created in 2000).

f) Robin Hanson invented the concepts of decision markets (PDF) and decision-aid markets.

g) Robin Hanson invented a new market design (for the 2000-2003&#8242-s Policy Analysis Market), the Market Scoring Rules, a mix between CDA and Scoring Rules &#8212-now in use for most enterprise prediction markets and public, play-money prediction exchanges. Note that MSR is mainly used in a one-dimension version, but many researchers are interested in its combinatorial version.

#4. Other Pioneering Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs

a) The Foresight Exchange was founded on September 22, 1994 by Ken Kittlitz, Sean Morgan, Mark James, Greg James, David McFadzean and Duane Hewitt. The Foresight Exchange is a play-money prediction exchange (betting exchange) managed by an open group of volunteers. It pioneered user-created and user-managed, play-money prediction markets. Any person can join the Foresight Exchange and interact with the rest of the Web-based organization. An independent judge (independent from the owner of the claim) should be appointed among the volunteers. [Thus, it’s not “DYI prediction markets”.]

b) The Hollywood Stock Exchange was founded on April 12, 1996, by Max Keiser and Michael Burns. See the patent for the Virtual Specialist. For more info, see: Is HSX the “longest continuously operating prediction market”??? &#8211- REDUX

c) BetFair was founded in 1999 by Andrew Black and Edward Wray, and was launched in England in June 2000. As of today, BetFair is the world&#8217-s biggest prediction exchange (betting exchange, event derivative exchange).

d) NewsFutures was founded in March 2000 and launched in September 2000 in France and in April 2001 in the US by Emile Servan-Shreiber and Maurice Balick. See: NewsFutures Timeline. NewsFutures was the first exchange to let people buy or sell contracts for each side of a binary-outcome event. The advantage of this design is that it avoids the need for &#8220-shorting&#8221-, a notion that tends to confuse novice traders. NewsFutures later extend that approach to deal with n-ary outcome events while implementing automatic arbitrage.

e) TradeSports was launched in Ireland in 2002 by John Delaney. InTrade was later purchased and became a non-sports prediction exchange (betting exchange). As of today, InTrade is the biggest betting exchange on the North-American market &#8212-where betting exchanges are still illegal. As for TradeSports, it closed at the end of 2008, alas.

#5. The Policy Analysis Market Brouhaha

a) Robin Hanson was the main economist behind the 2000–2003 US DoD&#8217-s DARPA&#8217-s IAO&#8217-s FutureMAP–Policy Analysis Market project. (For this project, Robin Hanson invented a new market design, the Market Scoring Rules.) On July 28, 2003, two Democratic US Senators called for the termination of PAM, the the big media gave airtime to their arguments, and the US DOD quickly ended the IAO&#8217-s FutureMAP program.

b) The second branch of the 2000–2003 US DoD&#8217-s DARPA&#8217-s IAO&#8217-s FutureMAP program was handled by the Iowa Electronic Markets and was intended to predict the SARS pandemic. (This project later gave birth to IEM&#8217-s Influenza Prediction Market.)

#6. James Surowiecki&#8217-s The Wisdom Of Crowds

a) James Surowiecki&#8217-s book, The Wisdom Of Crowds, was published in 2004.

b) Impact of The Wisdom Of Crowds.

#7. Recent Public Prediction Exchanges (Betting Exchanges, Event Derivative Exchanges) and Inventors/Innovators/Entrepreneurs

a) US-based and US-regulated HedgeStreet was launched in 2004 by John Nafeh, Russell Andersson, and Ursula Burger. A designated contract market (DCM) and a registered derivatives clearing organization (DCO), HedgeStreet is subject to regulatory oversight by the Commodity Futures Trading Commission (CFTC). In November 2006, IG Group bought HedgeStreet for $6 million.

b) Inkling Markets was launched in March 2006 and co-pioneered (with CrowdIQ, which later bellied up) the concept of DIY, play-money prediction markets.

c) In September 2006, TradeSports-InTrade was the first prediction exchange (betting exchange, event futures exchange) to apply Chris Masse&#8217-s concept of X Groups. See: TradeSports-InTrade prediction markets on Bush approval ratings.

d) HubDub was launched in early 2008 and is the second most popular play-money prediction exchange, behind HSX.

#8. Enterprise Prediction Markets

a) Until evidence of the contrary, it seems that Robin Hanson was the first to set up and run a corporate prediction exchange &#8212-at Xanadu, Inc., in April 1989. See: A 1990 Corporate Prediction Market + Anonymity is important for employees trading on internal prediction markets.

b) In the 1996&#8211-1999 period, HP ran a series of internal prediction markets to forecast the sales of its printers.

c) Eli Lilly sponsored 10 public, industry-level prediction markets in April 2003 (on the NewsFutures prediction exchange).

d) Eli Lilly began using internal prediction markets in February 2004 (powered by NewsFutures).

e) Google&#8216-s Bo Cowgill published about their use of internal prediction markets in October 2005.

f) Since then, many companies selling software services for enterprise prediction markets have been created.

#9. Disputes Between Traders And Exchanges

a) The scandal of the North Korean Missile prediction market that erupted in July 2006 is, as of today, the biggest scandal that rocked the field of prediction markets.

–

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

Posted on by
6

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

Robin Hanson on the Sim Exchange

Posted on by
Reply

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

simExchange a Keynesian Beauty Contest

Posted on by
4

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

Email Interview: Ken Kittlitz

Posted on by
7

My responses to a set of questions Chris Masse recently emailed to me:

Chris. F. Masse: Ken Kittlitz, you co-founded the Foresight Exchange (it went by the name &#8220-Idea Futures&#8221- at the time) in 1994. Would you mind telling me two words on your co-founders? Which ones brought the most into the project? Are you still in touch with them? Do you know what they have become?

Ken Kittlitz: David McFadzean got the ball rolling by bringing one of Robin Hanson&#8217-s early prediction market papers to our weekly discussion group. Sean Morgan realized that the WWW, then still in its infancy, would be a great way to create such a market. Mark James, along with Sean, did most of the coding of the initial prototype. Duane Hewitt and myself did most of the work on a paper and presentation that our group presented at a conference the following year.

I&#8217-m still in touch only with David- he&#8217-s currently a software architect at QuIC, a company that creates financial risk analysis/mitigation products.

CFM: What was the spirit of your group at that time (in 1994). Did &#8220-entrepreneurship&#8221- mean something for you, guys? Did you envision a commercial venture, or was it just collegians&#8217- play?

KK: Our weekly discussion group was known as the &#8220-BS Group&#8221- (Biological Simulation, in case you&#8217-re wondering), so I&#8217-d have to admit that &#8220-collegians&#8217- play&#8221- is a fair summary. In 1995, we did try to turn it into a commercial venture, which quickly revealed our lack of business experience. We were all techies of one sort or another, and techies often struggle in the business realm.

CFM: Would you mind telling me two words on GMU professor Robin Hanson? How would you introduce him to some of our readers (I pity them) who have never heard of him?

KK: Robin&#8217-s one of the smartest people I&#8217-ve ever met and, unlike many smart people, not over-specialized. He has deep understanding of a number of fields: artificial intelligence, physics, economics and likely a few others I&#8217-m not aware of. He has a habit of coming up with fascinating, controversial ideas, prediction markets being just one example.

CFM: You co-founded this play-money prediction exchange (Foresight Exchange) in 1994. In 1999/2000, Andrew Black and Edward Wray created and launched BetFair in England. BetFair became one of the most successful British start-ups and its two co-founders are now sitting pretty on a small fortune. In hindsight, don&#8217-t you think that you should have moved to the U.K. and incorporated the Foresight Exchange there, using real money?

KK: In hindsight, I think that I should have done a massively-leveraged short sale of NASDAQ stocks in March, 2000. :-)

The best way forward is always hard to identify, even with tools like prediction markets&#8230-

When we tried to commercialize the original &#8220-Idea Futures&#8221-, starting a real-money market offshore was certainly something we considered &#8212- though at that point, somewhere in the Caribbean seemed the likely venue. Even back then, it seemed likely that prediction markets would be considered a form of gambling, and hence subject to draconian restrictions. The Caribbean can be a nice place to live, but the prospect of never being able to return to North America to visit family and friends was quite a disincentive.

CFM: One thing that strikes me when visiting the Foresight Exchange is that you forbid sports prediction markets, which are very popular on the betting exchanges. Even Bo Cowgill&#8217-s group of Googlers trade on sports, sometimes &#8212-I believe. Sports trading can be fun. Are you a jock hater?

KK: Not really, but the Foresight Exchange was created primarily to focus on science and technology claims. Having it cluttered with a couple of dozen &#8220-tonight&#8217-s game&#8221- claims per day wasn&#8217-t too appealing.

CFM: If I can count, you have more than 12 years of experience in the field of prediction markets. You&#8217-ve seen them all, in all colors and shapes. Do you agree with what Robin Hanson said at the Yahoo! Confab, namely that the DARPA&#8217-s PAM scandal ignited interest in corporate prediction markets? Was the PAM scandal a &#8220-tipping point&#8221-?

KK: No. I think the real tipping point was the publication of James Surowiecki&#8217-s &#8220-The Wisdom of Crowds&#8221-. Those of us interested in prediction markets tend to overestimate the PAM controversy&#8217-s importance- it was a big deal for us, but only an incremental step in the general public&#8217-s awareness of the topic. The interest generated by Surowiecki&#8217-s book showed that prediction markets had &#8220-arrived&#8221- &#8212- they weren&#8217-t just of academic interest, but instead had real-world applicability.

CFM: Note that the DARPA&#8217-s PAM prediction markets was to be public. Which leads to my next question. You and partner David Perry at Consensus Point help Fortune-500 companies setting up and running their own internal prediction markets. Have you ever had the case where one firm opened its corporate prediction markets to contractors and clients?

KK: Some of the firms we deal with are certainly interested in having a fairly wide audience, including customers and contractors, for their markets. I can&#8217-t go into specifics at the moment, however.

CFM: How is Consensus Point doing, so far? Can you draw for us the portrait of the firm that wants to use internal prediction markets? Is it always to forecast sales? Do you sense that the requests come from senior executives or from mid-level prediction markets-enthusiast managers?

KK: Consensus Point is doing very well so far. A lot of inquiries do indeed originate from mid-level managers and researchers, but a fair number also come from the executive level. Sales forecasting is a popular application of the market, but project completion times and commodity price forecasting have also proved to be frequent questions.

CFM: Sorry to ask you this question bluntly. Would TradeSports and Betfair make great competitors of Consensus Point if ever they decided one day to sell prediction market services to organizations?

KK: Quite possibly, but it&#8217-s certainly not a given. Both companies have great trading platforms, but their expertise is in running real-money, public markets. Corporations aren&#8217-t really looking for that sort of domain knowledge when considering how to implement and use a prediction market.

CFM: Would you mind describing in a few words the prediction market services you sell? I guess it&#8217-s web-hosted CDA, but are some firms interested in web-hosted MSR?

KK: We offer both hosted and on-site installations of our software, as well as training, analysis and consulting services. As for MSR versus CDA, see below.

CFM: Speaking of Market Scoring Rules, why did you decide to use this design as the engine for the Washington Stock Exchange? What is its main competitive advantage to CDA? How can MSR best be described: &#8220-betting&#8221- or &#8220-simplified trading&#8221-?

KK: The line between an MSR and a CDA is thinner than you might think! We have a market maker for each stock that provides liquidity by placing bid and ask orders- this is a convenient way of implementing an MSR within a CDA framework. An MSR really helps to start (and keep) the market going, because people always have a price they can buy or sell at. With an unadorned CDA, the bid/ask spread can be enormous, and trading volumes very thin. This alas, is often the case on the Foresight Exchange.

I&#8217-d describe an MSR as allowing for &#8220-simplified trading&#8221- rather than &#8220-betting&#8221-, though I suppose it depends on how much thought the person interacting with it puts in!

CFM: Just curious. When a prediction exchange decides to use MSR, does it have to pay fees or royalties to its inventor, Robin Hanson?

KK: I don&#8217-t believe so, but Robin is in a far better position to answer that question than I am&#8230-

CFM: What is the biggest mistake (if any) you have made since the grand opening of Consensus Point? What did you learn from this big mistake?

KK: No really big mistakes come to mind. Of course, such things are often only obvious in retrospect, so ask me again in a few years.

CFM: What are corporate prediction markets competing against (if any)? Internal polls? Groups of in-house experts? The firm&#8217-s executives? Something else?

KK: Generally, the firm&#8217-s executives. We haven&#8217-t encountered too many cases where firms have been trying to use internal polls as part of their forecasting efforts.

CFM: Are you positive that corporate prediction markets will show something for it? Will the economics literature soon be filled with business cases on how firms can clearly benefit from using internal prediction markets?

KK: Based on my experiences in the field thus far, I&#8217-m confident that prediction markets will prove to compare favorably with the other forecasting methods companies use. This isn&#8217-t to say that they&#8217-ll always yield good information, or be the best thing to use in all situations, but I think they will turn out to be valuable.

Am I positive of this? Not absolutely. But then, I try not to be absolutely positive of anything!

CFM: Now, the question that kills. Tell me frankly. Are corporate prediction markets a &#8220-fad&#8221- or are they just started?

KK: Great question! I think it largely depends on how the prediction market community presents the ideas. There&#8217-s a very real danger that the topic will be over-hyped and, consequently, ultimately dismissed, just as so many other trendy business ideas have been in the past. Today&#8217-s darling is often tomorrow&#8217-s pariah. That would be a shame, since (obviously) I think the markets have a lot of merit.

Note by &#8220-prediction market community&#8221-, I&#8217-m referring not only to those who create and sell prediction markets and associated services, but also people who blog about the topic, create vortals, etc. Not mentioning any names here --) .

CFM: Are prediction markets just one forecasting tool, or do they have a bigger function, in your view?

KK: The pragmatist in me says they&#8217-re just one tool, albeit a great one. The idealist finds something profoundly appealing in their ability to democratize how information is gathered and, ultimately, how decisions are made. The idealist thinks they&#8217-re something more.

Prediction Markets Definitions – REDUX REDUX

Posted on by
15

No GravatarI would like to comment on the post from the Hatena Diary blog. (By the way, please note that my URL has changed, because I corrected one word in the post title. Sorry for the inconvenience.)

#1. Speculation-oriented prediction markets/exchanges: TradeSports, BetFair.

#2. Hedging-oriented prediction markets/exchanges: HedgeStreet and all the Chicago exchanges that will do binary, European call options.

#3. Forecast-oriented prediction markets/exchanges: Iowa Electronic Markets, AS CLAIMED BY THESE SCHOLARS WHOSE TASK WAS TO CONVINCE THE CFTC TO GRANT THEM A NO-ACTION LETTER. (They would have not gotten it, had they emphasized &#8220-speculation&#8221-. And, of course, &#8220-hedging&#8221- was out of question.) It&#8217-s a &#8220-claim&#8221- that might be discussed, since we&#8217-ve seen that TradeSports-InTrade is a much more powerful predictive tool for the US elections. Ditto for BetFair for U.K. elections.

#4. Decision-oriented prediction markets/exchanges: I would put here the kind of stuff that Robin Hanson is so excited about.

#5. Entertainment-oriented prediction markets/exchanges: Hollywood Stock Exchange, Washington Stock Exchange, Inkling, NewsFutures.

#6. Education-oriented prediction markets/exchanges: The Iowa Electronic Markets fits here, partially, regarding the use that professors around the country make of their markets in classrooms.

&#8212-

– I disagree with Google in #4. Maybe the Google internal prediction markets would fit in #3.

– I disagree with NewsFutures in #3 &#8212-I acknowledge (at least partially) the predictive power of play-money prediction exchanges, of course.

&#8212-

Should we judge markets/exchanges on INTENTIONS or on RESULTS? I don&#8217-t give a damn that TradeSports-InTrade and BetFair were created for speculation– if they have better predictive power than IEM, I&#8217-m fine with them. Ditto for the HSX. I don&#8217-t give the first fig that it was created as an entertainment tool. It&#8217-s the best forecasting tool for the movie business, period.

&#8212-

For the links to the prediction exchanges, see CFM.

&#8212-

Previous Blog Posts:

– Prediction Markets DEFINITIONS – not a “taxonomy”

– Professor Robin Hanson’s draft definitions is validated by professor Eric Zitzewitz.

– Prediction Markets Definitions – REDUX

– Prediction Markets Definitions – by Robin Hanson – 2006-11-21

&#8212-

Addendum: Robin Hanson has posted a comment&#8230-

“Oriented” is not clear enough for my tastes. Is this about trader motives? Trader results? Price results? Exchange motives?

&#8212-

My Answer: I meant &#8220-exchange motives&#8221-. [&#8230- See my comments. &#8230-] But now that I think of it, another classification taking account of the &#8220-price results&#8221- makes more sense.

Previous blog posts by Chris F. Masse: