Tag Archives: inkling markets

Inkling Markets, one year later

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Much, much better. Last year at the same time, in March 2007, I was selectively critical of some of the statements they did put in their (now old) version of their website. Adam Siegel has made good progress in mastering and conveying the problematic of enterprise prediction markets. I think that if Inkling Markets can truly deliver a service that can help companies mitigate business risks, and if they can prove positive results, then their client roll could be multiplied by a factor of 1,000 or so in the next 10 years.

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Adam Siegel:

Two years ago the only way to run a prediction marketplace was to roll your own or call a vendor/consultant and have them set up software and run markets for you. It took many weeks, often months. Today with Inkling Markets it take seconds. […]

[#1] Improve forecasting of key performance indicators
Track and raise awareness of key success metrics to identify and mitigate risk factors before it&#8217-s too late.

[#2] Expose product quality problems early
Identify design and production anomalies before a product (physical or virtual) is brought to market to avoid expensive repairs and recalls.

[#3] Predict risk to your supply chain
Run a &#8220-web&#8221- of markets about the risk factors to your supply chain to predict internal and external events that would cause inefficiencies or disruptions.

[#4] Foster a culture of innovation
Determine which new ideas and process improvements will have real business impact vs. the &#8220-nice to have.&#8221-

[#5] Create new interactions with users
Build a dedicated community of users around a marketplace of questions relevant to your business area and brand. […]

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Adam Siegel (Inkling Markets CEO) in Forbes:

[Prediction markets] can significantly:

  1. improve forecasts of key performance indicators,
  2. provide a more realistic understanding of project-completion dates,
  3. identify quality-control problems early in the development life cycle,
  4. improve demand forecasts within the supply chain,
  5. and allocate resources more appropriately across research-and-development projects.

[I have edited the formatting of this excerpt.]

Prediction markets on who is going to win an election are more accurate then the final Gallup poll.

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Signed: Eric Zitzewitz

Watch the video.

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

  • WARREN BUFFETT: I said that the US dollar might be “worth less” in five to ten years —not that it might be “worthless”.
  • The Year Of The Rat should bring $$$ to the prediction market industry and the event derivative traders.
  • WordPress founder Matt Mullenweg is my hero and so he should be yours.
  • InTrade-TradeSports has seen more than $50 million wagered on the U.S. presidential election.
  • LinkedIn will be data-mining its database of millions of users to find potential experts.
  • Britons can’t get enough of Yankees’ politics.
  • TURNING POINT: BARACK OBAMA EVENT DERIVATIVE NOW AHEAD FOR BOTH DEMOCRATIC NOMINATION AND NOVEMBER’S ELECTION.

The Industry Standard is powered by Consensus Point.

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I&#8217-m free to talk, now.

The Industry Standard is powered by Consensus Point.

The New York Times don&#8217-t print that, but they print that MIT CCI&#8217-s Thomas Malone (branded in the piece as a prediction market evangelizer) has been advising The Industry Standard.

I spotted dozens of news articles on the Industry Standard&#8217-s re-launching. Their spin doctor did a good job. :-D

By the way, speaking of media-managed prediction exchanges, the CNN prediction exchange has some prediction markets with each a total of transactions in the magnitude of 50,000. That&#8217-s awesome. Congrats to Inkling Markets. Mike Giberson (who has become an expert in MSR trading) is one of the traders, probably&#8230-

Our good doctor EJSS laughs at the Web 2.0″ concept on TechCrunch, but touts it as an essential part of the NewsFutures offerings on his website.

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Emile Servan-Schreiber of NewsFutures:

[&#8230-] Also, the mere idea of a Web 2.0 makeover of prediction markets is laughable. To paraphrase a good ol’ song from the 90’s, prediction markets were web 2.0 before web 2.0 was cool.

Yeah, but Emile advertises his mastering of &#8220-Web 2.0 tools&#8221- on the NewsFutures frontpage &#8212-while Inkling Markets and HubDug don&#8217-t even mention the &#8220-Web 2.0&#8243- concept on their frontpage (I checked).

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Here&#8217-s a screen shot of the NewsFutures website:

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NewsFutures Web 2.0

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Care to revise your TechCrunch statement, doc?

MP3 file

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

  • Pervez Musharraf prediction markets –Eric Zitzewitz Edition
  • The Over-Round Explained
  • WHY THE PREDICTION MARKETS WILL LIKELY F**K UP SUPER TUESDAY 2008.
  • Still unconvinced by prediction market journalist Justin Wolfers
  • Oprah Winfrey
  • RIGHT-CLICK THIS IMAGE, AND FILL IN THIS SURVEY, PLEASE.
  • Papers on Prediction Markets

NewsFutures do *NOT* favor event derivative management by traders.

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Emile Servan-Schreiber of NewsFutures:

January 29th, 2008 at 7:25 am

Another important difference with NewsFutures (where people have been “trading news” in 2000) is that hubdub doesn’t give away any prizes to performers. That, perhaps, is a direct consequence of the false good idea of letting people create their own markets. This not only creates many opportunities for fraud (if, for instance, the creator of the market also controls the outcome), but it also encourages incoherent outcome definitions, unverifiable outcomes, and duplicate or junkyard markets. Same problems that Inkling’s public markets suffer from.

Also, the mere idea of a Web 2.0 makeover of prediction markets is laughable. To paraphrase a good ol’ song from the 90’s, prediction markets were web 2.0 before web 2.0 was cool.

Emile Servan-Schreiber&#8217-s criticism is pertinent. However, his conclusion (&#8217-no&#8217- to self-management of event derivatives) is too radical. Without Inkling Markets, we wouldn&#8217-t have had Michael Giberson, who loves experimenting with play-money prediction markets. Somebody will come up, one day, with the right technology (e.g., a reputation system) patching the flaws that EJSS addresses. One day, in the future, we will be able to enjoy both worlds, because they will have merged into one: the libertarian prediction exchanges and the disciplined prediction exchanges.

My good doctor Emile, remember JFK, who pushed his country to do things &#8220-not only because they are easy, but because they are hard&#8220-, &#8230-and succeeded. :-D Just because event derivative management by traders is problematic does not mean that we should give up right now. Kudos to Inkling Markets and HubDub for trying, and acknowledging criticism from veterans. :-D

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UPDATE: Emile Servan-Schreiber comments&#8230-

No one has a monopoly on user-driven content. Every exchange out there lets people propose their own ideas for markets that might be of interest to themselves and others. For instance, on NewsFutures, a lot of the general forum discussion is back-and-forth between the users and the admins about which markets to create next. Where NF differs from FX, Inkling and Hubdub is that the NF admins (which, by the way, are recruited from the user-base itself) have the final control on wording as well as settlement. That&#8217-s what guarantees the coherence of the exchange, which in turn means we are able to offer prizes, whereas the likes of FX, Inkling and Hubdub likely cannot because they give too much control away to unknown entities to guarantee the fairness of the contest.

I like NewsFutures, and I get all that. But I&#8217-m saying that, nowadays, on the Web, people want DIY tools. That&#8217-s why HubDub and Inkling Markets are appealing to them. They don&#8217-t have to discuss &#8220-back-and-forth&#8221-. They create the event derivative they want. Straight from the producer to the trader.

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

  • RIGHT-CLICK THIS IMAGE, AND FILL IN THIS SURVEY, PLEASE.
  • Papers on Prediction Markets
  • The Journal of Prediction Markets
  • The 45-degree Line
  • Implied Probability of an Outcome –BetFair Edition
  • Justin Wolfers on Rudy Giuliani = not convincing… yet
  • The Florida primaries thru the prism of the InTrade prediction markets

Prediction market sessions of the OReilly Money-Tech Conference suffer fatally from the absence of the worlds most knowledgeable, most innovative and most trustworthy prediction market expert.

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O&#8217-Reilly Money-Tech Conference – 2008-02-06~07

Predicting the Future of Prediction Markets + Google as Prediction Market

Wharton&#8217-s Justin Wolfers, Google&#8217-s Bo Cowgill, Inkling&#8217-s Adam Siegel, and Sean Park (representing Himself).

No more Robin Hanson. :(

Better to stay home watching a re-play of the December 2006&#8217-s Yahoo! Confab, where Robin Hanson does appear.

– Confab Yahoo! on prediction markets – Streaming Video: 100k – 300k – 2006-12-13

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UPDATE: Robin Hanson comments&#8230-

I was invited, but the date conflicted with a SETI conference I&#8217-ll be speaking at.

Better Pricing for Tournament Prediction Markets

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Last year while working out a few thoughts on arbitrage opportunities in basketball tournament prediction markets at Inkling, it occurred to me that the Inkling pricing mechanism was just a little bit off for such applications. The question is whether something better can be done. An answer comes from the folks at Yahoo Research: yes.

Inkling’s markets come in a couple of flavors, so far as I know all using an automated market maker based on a logarithmic market scoring rule (LMSR). In the multi-outcome case – for example, a market to pick the winner of a 65-team single elimination tournament – the market ensures that all prices sum to exactly 100. If a purchase of team A shares causes its share price to increase by 5, then the prices of all 64 other team shares will decrease by a total of 5.

The logic of the LMSR doesn’t tell you exactly how to redistribute the counter-balancing price decreases. In Inkling’s case they appear to redistribute the counter-balancing price movements in proportion to each team’s previous share price (so, for example, a team with an initial price of 10 would decrease twice as much as a team with a previous price of 5). While for generic multi-outcome prediction markets this approach seems reasonable, it doesn’t seem right for a tournament structure. (I raised this point in a comment posted here at Midas Oracle last September, and responses in that comment thread by David Pennock and Chris Hibbert were helpful.)

The problem arises for pricing tournament markets because the tournament structure imposes certain relationships between teams that the generic pricing rule ignores. Incorporating the structure into the price rule in principle seems like the way to go. Robin Hanson, in his original articles on the LMSR, suggests a Bayes net could be used in such cases. Now three scientists at Yahoo Research have shown this approach works.

In “Pricing Combinatorial Markets For Tournaments,” Yiling Chen, Sharad Goel and David Pennock demonstrate that the pricing problem involved in running a LMSR-based combinatorial market for tournaments is computationally tractable so long as the shares are defined in a particular manner. In the abstract the authors report, “This is the first example of a tractable market-maker driven combinatorial market.”

An introduction to the broader research effort at Yahoo describes the “Bracketology” project in a less technical manner:

Fantasy stock market games are all the rage with Internet users…. Though many types of exchanges abound, they all operate in a similar fashion.

For the most part, each bet is managed independently, even when the bets are logically related. For example, picking Duke to win the final game of the NCAA college basketball tournament in your online office pool will not change the odds of Duke winning any of its earlier round games, even though that pick implies that Duke will have had to win all of those games to get to the finals.

This approach struck the Yahoo! Research team of Yiling Chen, Sharad Goel, George Levchenko, David Pennock and Daniel Reeves as fundamentally flawed. In a research project called “Bracketology,” they set about to create a “combinatorial market” that spreads information appropriately across logically related bets.…

In a standard market design, there are only about 400 possible betting options for the 63-game [sic] NCAA basketball tournament. But in a combinatorial market, where many more combinations are possible, the number of potential combinations is billions of billions. “That’s why you’ll never see anyone get every game right,” says Goel.…

At its core, the Bracketology project is about using a combinatorial approach to aggregate opinions in a more efficient manner. “I view it as collaborative problem solving,” Goel explains. “This kind of market collects lots of opinions from lots of people who have lots of information sources, in order to accurately determine the perceived likelihood of an event.”

Now that they know they can manage a 65-team single elimination tournament, I wonder about more complicated tournament structures. For example, how about a prediction market asking which Major League Baseball teams will reach the playoffs? Eight teams total advance, three division leaders and a wild-card team from the National League and the same from the American League. The wild-card team is the team with the best overall record in the league excepting the three division winners.

In principle the MLB case seems doable, though it would be a lot more complicated that a mere 65-team tournament that has only billions of billions of possible outcomes.

[NOTE: A longer version of this post appeared at Knowledge Problem as “At the intersection of prediction markets and basketball tournaments.”]

CNN Political Market = soon, the Planet Earths most traded play-money prediction exchange -after HSX.

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CNN Political Market

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Introduction

The goal of CNN Political Market is to combine the opinions of a diverse group of people to try and predict the probability of an event occurring or the value of something. Why is this important? Because more often than not, a diverse group of people or &#8220-crowd&#8221- will generate a more accurate prediction than an individual or a small group of &#8220-like-minded&#8221- or &#8220-single-discipline&#8221- folks.

In business, politics, and culture, this can have big ramifications:
– Predictions often turn out to be more accurate than surveys and polls-
– More accurate forecasts affect how marketing dollars are spent, how many widgets should be built in the first run, etc.-
– Decision making is more democratized, giving everyone input where they may not have had it before-
– Markets can serve as on-going indicators for key performance metrics.

Frequently Asked Questions

These are answers to questions we receive on a regular basis.
Q: What if I forgot my username or password?
A: It&#8217-s easy, just click here and new information will be sent to the email address we have for you.

Markets and Trading
Q: How do the prices in a market change?
A: Markets are guided by the forces of supply and demand. Every time a user buys a share in a particular idea or outcome, that demand forces the price up a little. The more people buy, the higher the price becomes. If the price gets too high, people will do the natural, self-interested thing and sell their shares to get a profit (or sell shares that they don&#8217-t own on credit). Similarly, each time a user sells a share, the price goes back down some.

Q: My math says I can buy more shares than the system lets me. Why?
A: Remember that for each share you buy, the price goes up some. If you&#8217-re buying a lot of shares at once, the last share in your order might cost significantly more than the first.

Q: I sold a block of shares, but I got less money out of it than I thought I would.
A: Just like the market price increases you see when you purchase shares, each share you sell drives the market price for those shares down a little. If you&#8217-re selling a lot of shares, the last share you sell be worth much less than the first.

Q: I think the current price in a market is reflective of what the market is trying to predict. What do I do now?
A: The best thing to do is to hold onto your shares. If you try to sell them, the market price will start to go down and you won&#8217-t make as much profit as you could if you wait for the market to close.

Balances
Q: What is &#8220-on credit?&#8221-
A: When you sell shares on credit you are betting that the market price of a stock is going to go down instead of up. The idea is to sell shares you don&#8217-t have at a high price, and buy them back later once the market price has fallen. You get to keep the difference as profit.

Because you never know how high a price will go up, we&#8217-ve set up specific rules for selling shares on credit so you don&#8217-t get yourself in to trouble:
– You can buy back shares you bought on credit with the money in your bank.
– There is a limit on how much stock you can sell on credit. You can figure out what that limit is by adding your available balance to the total value of shares you have bought. For example, if you have $10 available balance, and you also own $10 of stock, you can sell $20 of stock on credit. In other words, we try not to allow you to go in to debt by always protecting you against the worst possible scenario.

Q: How can I tell how much money I have?
A: Your balances are listed in the &#8220-total assets&#8221- box which you can find on your dashboard/portfolio. Your balance is also listed on each market trade page.

Q: How can I get more money?
A: You can earn money by trading wisely in markets. Look for good ideas that are undervalued, examine market descriptions for interesting things that others might not have noticed, or use your own unique, personal knowledge to make predictions that others can&#8217-t.

Q: What is the play money good for?
A: Status in the online trading community is based on how much money you have- just take a look at the &#8220-top traders.&#8221- The more money you have, the sooner everyone will begin to refer to you as &#8220-sage.&#8221-

Q: Can I give some of my money to another user?
A: Money is non-transferable – you must earn your own by trading.

Marketplace and Help
Q: The website looks a little funny. Is my computer supported?
A: We support the latest versions of Internet Explorer, Firefox, and Mozilla for Windows XP and 2000. For Mac OS X we support the latest versions of Safari, Firefox, and Mozilla. The application may work in alternate OSes and browsers, but we can&#8217-t make any promises.

CNN Political Market officially launches.

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As Chris alluded to a few days ago in a post, we&#8217-ve worked with CNN to launch a marketplace for this election season. A smattering of markets are available now with more to come, I&#8217-m told. So if you like trading in Inkling and want to participate in what I assume will quickly become our largest marketplace (it&#8217-s featured now on http://cnn.com and the inbound traffic is &#8220-remarkable&#8221- to say the least) you can go here: politicalmarket.cnn.com