The Now Economy

I have posted my slides from my talk about the Prediction Market summit, so I now feel free to bug others to post theirs. The Prediction Market Summit last week was quite a success. We had quite a variety of speakers. I led off the day by summarizing Zocalo’s current status, and showed a replay of an experimental session. I then pitched the idea that Prediction market operators should make their sites more searchable. This would raise the visibility of prediction markets generally, as well as their specific markets.

I spent the rest of my time explaining a way that Prediction markets based on claims with multiple exclusive outcomes should be presenting better prices to traders. These markets maintain a separate double auction for each outcome, segmenting the available order volume into non-interacting submarkets. Arbitrageurs are not a substitute for the market in offering these trading opportunities, since riskless arbitrage can’t take advantage of interest that never appears in the order book. After a few hallway conversations I think most people understood the argument.

Bo Cowgill talked about Google’s internal markets. They wrote their own software from scratch, following the IEM model. Traders buy a basket of claims in order to sell a claim. Usability and politics were the biggest issues for them. The company contributes money in an account for each Google employee, which they can then trade. Each participant’s account is cashed out at the end of each quarter. They get as many lottery tickets as they had cash from liquidating claims. (i.e. money you don’t invest doesn’t earn anything in the lottery.) Prizes are then awarded to lottery winners; this eliminates the incentive (common in play money markets with prizes for top performers) to take extreme chances in order to boost your odds of being the single top performer. A legal issue they had to contend with in selecting claims to bet on was that information on some outcomes is controlled by the SEC. If employees find out what is happening in some areas, they might become subject to SEC rules for insiders, and their stock trading restricted. The operators of the market chose subjects where that likelihood seemed small.

Bernardo Huberman presented work at HP on techniques for using games to elicit trader’s risk preferences and subject knowledge, and then use nonlinear functions to aggregate their predictions. This approach can address problems due to illiquidity when there are few traders, and prevent manipulation. Bernardo reported that HP is starting to use some internal markets to predict price and availability of various PC components on which the company depends.

Emile Servan-Schreiber reported that the prediction market business climate is improving. NewsFutures has been getting better responses as they sell the concept within businesses. He listed Dentsu, Lilly, Mars, Abbot, Yahoo, and the World Economic Forum as customers who are currently using their software.

Mike Knesevitch talked about TEN’s (Trade Exchange Network, also TradeSports, and InTrade) markets. The fact that they trade in real money allows investors to hedge. Mike said their sports markets are extremely efficient because there are a number of arbitrageurs who know the statistical relations between various outcome, and take advantage whenever prices exceed certain bounds. Since they don’t take a position in any of the trades, Mike said they aren’t subject to the 1961 Wire act, which regulates interstate gambling in the US. It also means they couldn’t get a bookie’s license in the UK if they wanted one. TEN has approval from the CFTC to operate as an exempt Board of Trade. eBOTs can only support trading between certain large firms and qualified investors. My understanding of what Mike said is that TEN intends to operate a separate exchange for these large players, allowing them to hedge positions by trading in prediction markets. One area TEN intends to grow in is weather contracts. Mike said TEN, as one of their criteria for approving a new claim, looks for natural trading partners who would take opposite positions. He pointed out that Ski resorts (whose business falls in a light snow year) have exposure that is opposite to that of big cold weather cities (whose snow removal expenses grow in a heavy snow year.)

Russell Anderson talked about HedgeStreet’s markets. One factoid I picked up is that HedgeStreet gets their piece by charging a percentage of the winning side of contracts. TEN charges a commission to traders who buy at the market price. Orders entered into the book are free.

Eric Zitzewitz presented his paper with Justin Wolfers on Interpreting Prediction Market Prices as Probabilities. This paper is a response to Charles Manski’s earlier paper arguing that prices are more likely to constitute a weighted average of beliefs. Eric argued that a more general model of trader’s preferences and budget leads to a model in which prices are very close to probabilities, and that traders have practical incentives to move the prices closer to probabilities. The paper shows that their model also predicts price curves that match the results seen in actual markets more closely than Manski’s do. One good line that Eric used in explaining the uses for Prediction Markets is that they allow us to study the likelihood of events even when the events never actually take place.

Todd Proebsting has been proselytizing for Prediction Markets inside Microsoft for a couple of years. He set up markets that continue to be used for internal decision making, though not in any formal routine process. The first market they ran quickly showed that a project was in serious schedule trouble, even though the management team had been reassured (by the same employees who participated in the market) that the project was on track. Unfortunately for the people who predicted the schedule problem, the project manager changed the milestones in response to the dire predictions, eliminating the value of the investments based on the completion date. Since then, Todd has been more careful about how questions are phrased. Microsoft’s markets uses a market maker and doesn’t support limit orders because their initial informal survey showed that people were hesitant to leave book orders. Todd recently saw Edward Tufte’s presentation on the evils of PowerPoint, so he spoke without slides which might have been illegal if he tried to do it at Microsoft.

Dave Pennock gave the audience a choice among a few short presentations he had prepared. The audience opted first for his presentation on Search Futures and the Tech Buzz game. The Tech Buzz forecasts got better as deadlines drew nearer. Some traders were able to figure out that the prices in the Dynamic Parimutuel market should be proportional to the square root of the underlying index value (search terms on Yahoo); the best traders pushed prices closer to that level. The second section of the talk covered the paper Pennock wrote with Servan-Schreiber, Wolfers, and Galebach. They analyzed data from real money and play money prediction markets for NFL football and showed that the prices on both were much better predictions than those of most bettors. (NewsFutures and TradeSports came in 6th and 8th out of about 2000 contestants.)

The day ended with a panel that I moderated. I didn’t get a chance to take notes, so all I can say was that it was congenial, and the panelists addressed all the questions.

The format was generous, with plenty of time between sessions for people to talk. The location at UCSF’s Mission Bay campus worked quite well.

Congrats! - an amazing mention for a pre-release service… Looks like the buzz campaign is working well for Adam and Joyce, and a tip of the hat to the whole Renkoo team for making such a polished impression on no less than Mike Langberg.

InternetNews also covered the demo, with a zinger from Esthr at the end.

By Mike Langberg, Mercury News Wed, Dec. 07, 2005

… Of the several start-ups presenting at When 2.0, my favorite was Renkoo.

The Palo Alto company plans to launch an online service early next year that will provide a shared space for small groups to plan events.

If you want to invite a list of friends to a party with a fixed time and place, it’s easy to use the existing Evite service. But Evite doesn’t work well when you’re not sure what you want to do, or what your friends prefer.

With Renkoo, you can send a query by e-mail, instant message or cell-phone text message, perhaps asking, “Who wants to go for a hike this weekend? What’s the best time for you, and where do you want go?'’

Your friends then reply with their preferences, and the group goes back and forth — with the dialogue recorded on a single Web page — until there’s a consensus.

Renkoo, named for a form of Japanese poetry called renku or renga where people take turns writing verses, will be free to users and hopes to make money through ads and sponsorships.

Adam Rifkin, Renkoo’s co-founder and chief executive officer, said he aims to solve a basic problem: “You can never get enough information on what your friends are doing.'’

While it’s much too soon to know whether Renkoo or any of the other bold proposals at When 2.0 will succeed, the vision at least is clear.

In a few years, we’ll effortlessly manage our time by entering appointments on whatever Internet-connected electronic device is at hand — a computer or a cell phone or a personal digital assistant — and those appointments will instantly appear on the calendars of others we designate.

If we change the time of an appointment, it will instantly update the calendars of others.

Public and group events we want to track, from upcoming rock concerts and professional hockey games to our children’s soccer team schedules, will automatically pop into our calendars.

There are lots of technical, security and privacy issues yet to resolve, but the benefits are big enough that families may ultimately be freed from running their lives through scraps of paper stuck to refrigerator doors.

By David Needle

Rather than manage events already planned, Renkoo focuses on making events happen. “We bring friends together in the process,” CEO Adam Rifkin told internetnews.com.

He said services like Evite are for larger group functions that already have a fixed time and place. With Renkoo there is, among other features, a real-time voting mechanism, so people can decide on a time for lunch, movie or other gathering. The original planner can decide when to rein in the votes and chatter in order to set the details of where and when. Renkoo also accepts SMS text messaging, and it’s experimenting with links to instant messaging services as part of the site.

While many of the vendors were optimistic that they could break new ground on the consumer side, at least one attendee was skeptical.

“These things are great if you’re an extrovert,” said Chris Nesladek, a user interface designer for Intuit. “But you’re only organized if you have responsibility. For a lot of 18- to 24-year-olds, having a calendar or updating your schedule doesn’t matter.

For young and old alike, Dyson had this comment worth considering in a recent edition of her Release 1.0 newsletter: “You can’t create time. You can only steal it, reallocate it, use it or waste it.”

The Prediction Market Summit that CommerceNet sponsored in San Francisco last week was quite a success. There were 9 speakers, including four that I hadn’t heard before. I’ll have more to say about the talks and I’d like to post some of the pictures I took, but I’m going to have to dole it out over several days so I can get other work done. The first thing I want to take care of is posting my slides. I dropped out of PowerPoint twice, so I want to make a version of those exhibits that I can present with the slides. The first time I dropped out of PowerPoint was to show a replay of a session of an experiment the folks at GMU ran using Zocalo in early November.

In the experiment, forecasters watch the market interaction, and try to decide whether the value of the tickets being traded is 0 or 100. 4 pure traders and 4 manipulators are active in the market. Each starts out with two tickets and 200 units of currency. Both the traders and the manipulators have each been given a hint (the hints are true with 2/3 chance) as to the actual value of the tickets. The manipulators have an additional incentive to make the forecasters believe that the asset has one value or another. Sometimes the incentive is consistent with the hint, sometimes not.

You can see the replay here. The javascript that drives it only works in FireFox, so you won’t be able to view it with other browsers. (I will look into getting a quicktime or other movie made.) The image above displays the contents of the order book (green and orange dots) at the time of each transaction (black dots). The UI that the experimental subjects see only shows the current contents of the order book. Notice that the order book in the center of the screen updates along with the colored dots in the strip chart. The “immediate order” buttons are updated as orders are entered and filled.

I created the depiction above in hopes that the extra context it gives would be useful for figuring out how much interest there is on each side of the market.

Following up on our recent release of a long-delayed tech report on social ranking of email search, another news article recently highlighted a similar approach to a different aspect of the problem, socially sorting incoming email.

In either case, there’s a crying need for smarter email clients (at least, for us few doddering old souls who live and die by email — apparently, few creatures under 18 have ever heard of the medium, between their gum-chewing, IMing, and illegal downloading…). As Microsoft Research sociologist Marc Smith points out in the news report on the SNARF system, there’s already an immense reservoir of personal behavioral information on the average PC hard drive. Taking advantage of this information to surface implicit relationships between correspondents, whether based on a graph analysis (as our KudoRank proposal does); interaction timelines (apparently a key part of SNARF and its USENET predecessor, NetScan); or the kinds of vocabulary and relationships used (Andrew McCallum’s Author-Role-Topic model); are all signs of a trend to put the vast computing resources available today to work on the treacherous problem of getting computers to read email for us

SNARF begins indexing e-mail messages on initial launch. Once it’s finished indexing, it shows a window with three panes.

• Top pane: People who have sent recent e-mail addressed or cc’d to the mailbox owner. Messages are unread.
• Middle pane: People who have sent recent, unread e-mail addressed to anyone.
• Bottom pane: All people mentioned in any e-mail the mailbox owner has received in the past week.

SNARFing your way through e-mail
By Ina Fried
Story last modified Fri Dec 02 04:00:00 PST 2005

With the world’s in-boxes overflowing with unread messages, researchers at Microsoft are offering up a tool they hope will help people sort through the morass.

The software maker this week released a free utility that aims to sort e-mail in a new way: It can organize messages not just by how recent they are, but also by whether the recipient knows the sender well.

The program, known as SNARF, bases its approach on the fact that people tend to interact more with messages from those they care about.

“You don’t respond to everybody, and not everybody responds to you,” said Marc Smith, one of the Microsoft researchers who developed SNARF, or Social Network And Relationship Finder.

Though SNARF is a research project for now, Microsoft said that similar features could soon make their way into its e-mail products.

Smith boils it down this way. His computer, for all its power, serves up his e-mail without distinguishing junk mail from messages sent by close friends. His dog, on the other hand, learns who his friends are and stops barking at them.

“If my dog can tell who strangers are, apart from friends…my e-mail reader should be able to do the same,” he said.

The task is increasingly important as people become overloaded with e-mail. Though many like to be alerted to new messages, the barrage of notifications is now so frequent for many workers that it is nearly impossible to get any creative work done without being interrupted. SNARF screenshots

“The machines got us into this problem,” Smith said. “They are going to have to get us out of it.”

Smith calls today’s method of sorting e-mail the “ADD sort order,” in which the newest messages are constantly presented first, regardless of who sent them. There has to be a better way, he said.

Figuring out who your friends are may not seem like a task well-suited to computers, but Smith said it’s simply a matter of making sure that the computer is adding up the right things.

“The beautiful thing about computers is that they are really, at their core, accounting machines. They love to count things. Social relationships are countable,” Smith said.

In SNARF’s case, the software looks at how often people correspond with particular content in the body of a message and how often they reply to one another’s correspondence, among other things.

The concept is not new. The idea of “social sorting” has been explored by Microsoft and others for years. Researchers at Hewlett-Packard, for example, looked at the patterns of who e-mailed who within HP Labs. Doing so, the researchers found, turned out to be a more effective means of determining working groups than looking at an organizational chart.

Microsoft has also used social sorting to help users wade through Internet forums, in a research effort known as NetScan.

Smith points out that our PCs already know tons about us, in many cases storing years’ worth of messages and replies. “This is more than the diarists of the 17th and 18th centuries,” he said.

SNARF can also sort messages based on whether they were sent directly to you, whether you were copied on the message or whether you were part of a distribution list.

While such an approach can help sort through the sea of messages, it’s not flawless. Smith noted that not everyone who is important to him returns his e-mails.

“My mother, I’m sorry to say, just never replies to my e-mail,” he said, quickly noting that it’s no reflection on the quality of his relationship with her.

Smith said there is a strong chance the social sorting techniques will find their way into Microsoft products. There have been feelers from the teams responsible for Outlook, Exchange, Hotmail and Outlook Express, he said.

“We’re having lots of meetings with people,” Smith said.

For now, the research team has put its software out there as a download for people to experiment with. Officially, Microsoft says SNARF will definitely work with Outlook 2003 and Windows XP Service Pack 2, though Smith said it may work with other software. SNARF also requires the .Net framework, though it will install it if a computer does not already have the operating system add-on.

Smith is also working on expanding the research project in several ways. For example, the current version cannot be customized so that a user can say that a certain friend is important, even though they only exchange e-mail once a year.

Allowing users to “tag” e-mails in various ways is among the features that the company is looking at. “We are exploring a range of ideas around that,” he said. “It’s a very important direction,” he added, noting that the next version of Outlook also includes new tagging capabilities.

Moving onto cell phones would be another good move for SNARF, he said. “If you are not at your computer to do triage, having 150 e-mails can be daunting,” he said. “It would be nice to have the seven e-mails from colleagues in a separate folder.”

Chris Masse sent me a pointer to Marco Ottaviani’s draft announcement for a Mini-Conference on Information and Prediction Markets to be held December 19 in London. That’s so little notice, and so close to Christmas that I’m not seriously contemplating attending, but the list of speakers is another good one. If London isn’t a long trip for you, think about this one.

• Paul Tetlock: Designing Information Markets for Decision Making
• Robin Hanson: Comparing Ways to Encourage Information Market Participation
• Leighton Vaughan-Williams: Efficiency in Exchange Betting Markets
• Olivier Gergaud: Strategic Forecasting in Rank-Order Tournaments
• Frederic Koessler: Individual Behavior and Beliefs in Experimental Parimutuel Betting Markets
• Justin Wolfers: Interpreting Prediction Market Prices as Probabilities
• Peter Norman Sorensen: Aggregation of Information and Beliefs in Prediction Markets
• Erik Snowberg: Partisan Impacts on the Stockmarket
• Koleman Strumpf: Manipulating Political Stock Markets
• Eric Zitzewitz: Full Distribution Event Studies

It’s nice to see the number of conferences and workshops in this area growing.

The Prediction Markets summit that will be held in San Francisco on December 2nd is shaping up to be quite an event. There will be speakers from Google, HP, NewsFutures, Trade Exchange Network, HedgeStreet, Stanford, Microsoft, and Yahoo. I’ll start things off by telling what I’ve been able to do with Zocalo so far, and then challenge the other attendees on a few points of Prediction Market design. Bernardo Huberman of HP will give the keynote. Google and Microsoft will talk about their experiences with markets inside the corporation. Representatives of NewsFutures, InTrade, HedgeStreet, and Yahoo will talk about how they are faring in the market. Eric Zitzewitz of Stanford will present a paper responding to Manski’s charge that prices in prediction markets don’t reflect probabilities.

The day will end with a panel discusssion, which I will facilitate. I’ll ask about Tom Bell’s draft legislation, about the prospects for increasing liquidity on HedgeStreet, and I’ll try to get InTrade to say what they plan for their proposed US subsidiary if they haven’t talked about that earlier in the day.

This will be the first public opportunity that I’m aware of to see presentations on Google’s markets, HedgeStreet, or InTrade. There is still space available. If you are at all interested in Prediction Markets, you should register now.

The whole event is billed as having a conversational, interactive style, so if you want to find out more about these ventures, this will be the place. Future events in the series are planned for the east coast, Europe, and Asia, but they’ll have very different speaker line-ups.

Tom Bell posted a short draft (with variations) of a bill legalizing Prediction Markets. The bill’s focus is explicitly on markets for science, technology, and public policy, so it would benefit the Simon Exchange and possibly the Washington Stock Exchange, but not other, general purpose, markets. The strongest version’s provisions are really simple: no federal, state, or local government may enact or enforce laws to regulate prediction exchanges, and standard commercial law continues to hold regarding the contracts. (The limitation to claims on science, technology, and public policy is in the definitions.) The weakest version only forbids enforcement against prediction markets of laws concerning gambling, commodities futures, securities, or insurance. I’ve simplified the legalese in order to get it to a couple of lines. Tom’s version is only a little longer in order to have all the necessary legalese.

These would be very nice rules if they were law, but the more interesting question is what it would take to get them enacted. Congress isn’t in the business of enacting legislation merely because it would make us all freer; there has to be a substantial lobby, or evidence of plenty of interest to make it happen. In order to get the support of the relevant industry (Trade Exchange Network, ProTrade), the terms would have to be opened up to include more than just science and technology. So a big question is whether enough support could be lined up with a version limited to science and technology to get a bill passed (it should be easier because the subjects are respectable, and can be pitched as “not like gambling”), or whether having additional companies backing it would help more. I wouldn’t mind letting the sports markets join the party, as long as it makes it easier for a bill to pass. If no bill is going to pass, it doesn’t make a difference anyway, and we’re left looking for legal strategies that will allow public policy markets to avoid a suit or survive one if it happens.

… there’s money to be made in adult content, so eventually handsets will become yet another commercial outlet. Rather than adopting a Web-standard content rating platform such as PICS, the wireless industry associaton (CTIA) has come out with some as-yet-unspecified new technology. So far, it appears to only be a press event about how nice it will be once it’s all working.

See the Washington Post or the New York Times for largely similar content-free announcement stories. From the NYT piece:

The nation’s major cellular phone carriers said yesterday that they had adopted a content rating system for video, music, pictures and games that they sell to cellphone users - a development that could pave the way for them to begin selling pornography and sex-oriented content on mobile devices. The carriers said the ratings, meant to mimic content classifications for movies and video games, are voluntary. Initially, the carriers would classify content in two categories: general interest and restricted content deemed appropriate only for people over the age of 18. The carriers said they had agreed not to begin making restricted content available until they had developed filters and other technological tools that would enable parents to prevent children from getting access to inappropriate material. The carriers, including Cingular Wireless and Verizon Wireless, the largest and second-largest mobile companies, said they were developing filtering technology and that it should be available soon.