All posts by David Pennock

WeatherBill shows the way toward usable combinatorial prediction markets

WeatherBill let’s you construct an enormous variety of insurance contracts related to weather. For example, the screenshot embedded below shows how I might have insured my vacation at the New Jersey shore:

Read this document on Scribd: WeatherBill Example Contract

For $42.62 I could have arranged to be paid $100 per day of rain during my vacation.

(I didn’t actually purchase this mainly because the US government insists that I am a menace to myself and should not be allowed to enter into such a dangerous gamble — more on this later. And as Dan Reeves pointed out to me, it’s probably not rational to do for small sums.)

WeatherBill is an example of the evolution of financial exchanges as they embrace technology.

WeatherBill can be thought of as expressive insurance, a financial category no doubt poised for growth and a wonderful example of how computer science algorithms are finally supplanting the centuries-old exchange logic designed for humans (CombineNet is another great example).

WeatherBill can also be thought of as a combinatorial prediction market with an automated market maker, a viewpoint I’ll expand on now.

On WeatherBill, you piece together contracts by specifying a series of attributes: date range, place, type of weather, threshold temperature or participation level, minimum and maximum number of bad-weather days, etc. The user interface is extremely well done: a straightforward series of adaptive menu choices and text entry fields guide the customer through the selection process.

This flexibility quickly leads to a combinatorial explosion: given the choices on the site I’m sure the number of possible contracts you can construct runs into the millions.

Once you’ve defined when you want to be paid — according to whatever definition of bad weather makes sense for you or your business — you choose how much you want to be paid.

Finally, given all this information, WeatherBill quotes a price for your custom insurance contract, in effect the maximum amount you will lose if bad weather doesn’t materialize. Quotes are instantaneous — essentially WeatherBill is an automated market maker always willing to trade at some price on any of millions of contracts.

Side note: On WeatherBill, you control the magnitude of your bet by choosing how much you want to be paid. In a typical prediction market, you control magnitude by choosing how many shares to trade. In our own prediction market Yoopick, you control magnitude by choosing the maximum amount you are willing to lose. All three approaches are equivalent, and what’s best depends on context. I would argue that the WeatherBill and Yoopick approaches are simpler to understand, requiring less indirection. The WeatherBill approach seems most natural in an insurance context and the Yoopick approach in a gambling context.

How does the WeatherBill market maker determine prices? I don’t know the details, but their FAQ says that prices change “due to a number of factors, including WeatherBill forecast data, weather simulation, and recent Contract sales”. Certainly historical data plays an important role — in fact, with every price quote WeatherBill tells you what you would have been paid in years past. They allow contracts as few as four days into the future, so I imagine they incorporate current weather forecasts. And the FAQ implies that some form of market feedback occurs, raising prices on contract terms that are in high demand.

Interface is important. WeatherBill shows that a very complicated combinatorial market can be presented in a natural and intuitive way. Though greater expressiveness can mean greater complexity and confusion, Tuomas Sandholm is fond of pointing out that, when done right, expressiveness actually simplifies things by allowing users to speak in terms they are familiar with. WeatherBill — and to an extent Yoopick IMHO — are examples of this somewhat counterintuitive principle at work.

There is another quote from WeatherBill’s FAQ that alludes to an even higher degree of combinatorics coming soon:

Currently you can only price contracts based on one weather measurement. We’re working on making it possible to use more than one measurement, and hope to make it available soon.

If so, I can imagine the number of possible insurance contracts quickly growing into the billions or more with prices hinging on interdependencies among weather events.

Finally, back to the US government treating me like a child. It turns out that only a very limited set of people can buy contracts on WeatherBill, mainly businesses and multi-millionaires who aren’t speculators. In fact, the rules of who can play are a convoluted jumble that I believe are based on regulations from the US Commodity Futures Trading Commission.

Luckily, WeatherBill provides a nice “choose your own adventure” style navigation flow to determine whether you are allowed to participate. Most people will quickly find they are not eligible. (I don’t officially endorse the CYOA standard of re-starting over and over again until you pass.)

Even if red tape locks the average consumer out of direct access, clever companies are stepping in to mediate. In a nice intro piece on WeatherBill, Newsweek mentions that Priceline used WeatherBill to back a “Sunshine Guaranteed” promotion offering refunds to customers whose trips were rained out.

Can you think of other end-arounds to bring WeatherBill functionality to the masses? What other forms of expressive insurance would you like to see?

Predict Olympic medal counts on Yoopick

We just added a new feature to Yoopick designed especially for Frenchmen Chris and Emile and citizens of nineteen other countries to place their swagor* on how many Olympic medals they think their country will win.

We’ve argued that the Yoopick interface is useful for predicting almost any kind of number, and since medal count is indeed a number, we thought we’d give it a try.

Besides, Lance told us it would be a good idea.

Sign up, play, enjoy, and don’t forget to tell us what you think!

Thanks,
Sharad Goel
David Pennock
Dan Reeves

* Scientific wild-ass guess, on record

Yoopick: Olympic medal count: Select

Yoopick: Olympics medal count: France: Make pick

The seedy side of Amazon's Mechanical Turk

I mostly side with Lukas and Panos on the fantastic potential of Amazon’s Mechanical Turk, a crowdsourcing service specializing in tiny payments for simple tasks that require human brainpower, like labeling images. Within the field of computer science alone, this type of service will revolutionize how empirical research is done in communities from CHI to SIGIR, powering unprecedented speed and scale at low cost (here are two examples). My guess is that the impact will be even larger in the social sciences; already, a number of folks in Yahoo’s Social Dynamics research group have started running studies on mturk. (A side question is how university review boards will react.)

However there is a seedier side to mturk, and I’m of two minds about it. Some people use the service to hire sockpuppets to enter bogus ratings and reviews about their products and engage in other forms of spam. (Actually this appears to violate mturk’s stated policies.)

For example, Samuel Deskin is offering up to ten cents to turkers willing to promote his new personalized start page samfind.

EARN TEN CENTS WITH THE BONUS – EASY MONEY – JUST VOTE FOR US AND COMMENT ABOUT US

EARN FOUR CENTS IF YOU:

1. Set up an anoymous email account likke gmail or yahoo so you can register on #2 anonymously

2. Visit http://thesearchrace.com/signup.php and sign up for an account – using your anonymous email account.

3. Visit http://www.thesearchrace.com/recent.php and vote for:

samfind

By clcking “Pick”

SIX CENTS BONUS:

4. Visit the COMMENTS Page on The Search Race, it is the Button Right Next to “Picks” on this page: http://www.thesearchrace.com/recent.php and

5. Say something awesome about samfind (http://samfind.com) on The Search Race’s Comments page.

Make sure to:

1. Tell us that you Picked us.
2. Copy and Paste the Comment you typed on The Search Race’s Comment page here so we know you wrote it and we will give you the bonus!

In fact, Deskin is currently offering bounties on mturk for a number of different spammy activities to promote his site. On the other hand, what Deskin is doing is not illegal and is arguably not all that different than paying PRWEB to publish his rah-rah press release (Start-up, samfind, Launches Customizable Startpage to Compete with Google, Yahoo & MSN, Los Angeles, California (PRWEB) August 4, 2008). And I have to at least give him credit for offering the money under his own name.

Another type of task on mturk involves taking a piece of text and paraphrasing it so that the words are different but the meaning remains the same. Here is an example:

Paraphrase This Paragraph

Here’s the original paragraph:

You’re probably wondering how to apply a wrinkle filler to your skin. The good news is that it’s easy! There are a number of different products on the market for anti aging skin care. Each one comes with its own special application instructions, which you should always make sure to read and carefully follow. In general, however, most anti aging skin care products are simply applied to the skin and left to soak in.

Requirements:
1. Use the same writing style as much as possible.
2. Vary at least 50% of the words and phrases – but keep the same concepts. Use obviously different sentences! Your paragraph should not be just a copy of the first with a few word replacements.
3. Any keywords listed in bold in the above paragraph must be included in your paraphrase.
4. The above paragraph contains 75 words… yours must contain at least 64 words and not more than 101 words.
5. Write using American English.
6. No obvious spelling or grammar mistakes. Please use a spell-checker before submitting. A free online spell checker can be found at www.spellcheck.net.

If you find it easier to paraphrase sentence-by-sentence, then do that. Please do not enter anything in the textbox other than your written paragraph. Thanks!

I have no direct evidence, but I imagine such a task is used to create splogs (I once found what seems like such a “paraphrasing splog”), ad traps, email spam, or other plagiarized content.

It’s possible that paid spam is hitting my blog (either that or I’m overly paranoid). I’m beginning to receive comments that are almost surely coming from humans, both because they clearly reference the content of the post and because they pass the re-captcha test. However, the author’s URL seems to point to an ad trap. I wonder if these commenters (who are particularly hard to catch — you have to bother to click on the author URL) are paid workers of some crowdsourcing service?

Can and should Amazon try to filter away these kinds dubious uses of Mechanical Turk? Or is it better to have this inevitable form of economic activity out in the open? One could argue that at least systems like mturk impose a tax on pollution and spam, something long argued as an economic force to reduce spam.

My main objection to these activities is the lack of disclosure. Advertisements and press releases are paid for, but everyone knows it, and usually the funding source is known. However, the ratings, reviews, and paraphrased text coming out of mturk masquerade as authentic opinions and original content. I absolutely want mturk to succeed — it’s an innovative service of tremendous value, one of many to come out of Amazon recently — but I believe Amazon is risking a minor PR backlash by allowing these activities to flow through its servers and by profiting from them.

Some recent news and notes on prediction markets

A collection of (relatively) recent yellow bricks on the road to widespread use of prediction markets:

Plus a Murphy’s Law Alert:

Mr. Murphy may be hard at work orchestrating one of his signature ironies. Picture this: Prediction market proponents (including me) aren’t careful and get what they wish for: The CFTC takes prediction markets under its regulatory purview. Then, efforts to legalize Internet gambling in the US succeed, opening up an enormous and fabulously lucrative business that the “socially good” prediction market operators are legislated out of, mired instead in a separate regulatory goop of their own making.

26 comments released from purgatory

Sorry folks, I just released 26 comments from purgatory where they had been sitting for as long as 58 days. All pending comments have now been approved and posted. I’ll try to go through them soon and respond where appropriate.

About two months ago I changed my WordPress configuration and it turns out that comments were piling up for moderation without email notification, and I failed to spot the growing queue until now.

Since I’m using re-captcha and have turned off trackbacks, I shouldn’t need to moderate comments going forward, so I’ve turned off moderation (fingers crossed).

Yoopick: A sports prediction contest on Facebook with a research twist

I’m happy to announce the public beta launch of Yoopick, a sports prediction contest with a twist.

You pick any range you think the score difference or point spread of the game will fall into, for example you might pick Pittsburgh wins by between 2 and 11 points.

Yoopick make your pick slider interface screenshot

The more your prediction is viewed as unlikely by others, and the more you’re willing to stake on your prediction, the more you stand to gain. Of course it’s all for fun: you win and lose bragging rights only.

You can play with and against your friends on Facebook.

You can settle a pick even before the game is over, much like selling a stock in the stock market. Depending on what other players have done in the interim, you may be left with a gain or loss. You gain if you were one of the first to pick a popular outcome.

If you run out of credit, you can “work off your debt” by helping to digitize old books via the recaptcha project.

Those are the highlights if you want to go play the game. If you’re interested in more details, read on…

Motivation, Design, and Research Goals

There are a great many sources of sports predictions, including expert communities, statistical number crunchers, bookmakers, and betting exchanges. Many of these sources are highly accurate, however they typically focus on predicting the outright or spread-adjusted winner of the game. Our goal is to obtain more information about the final score, including the relative likelihood of each point spread. For example, if our system is working, on average there should be more weight put on point spreads of 3 and 7 in NFL games than on 2,4,6, or 8.

We chose sports as a test domain to tap into the avid fan base and the armies of arm chair (and Aeron chair) prognosticators out there. However, the same approach should translate well to any situation where you’d like to predict a number, for example, the vote share of a politician or the volume of sales of your company’s widget. In addition to giving you the expected value of the number, our approach gives you the confidence or variance of the prediction — in fact, it gives you the entire probability distribution, or the likelihood of every possible value of the number.

Underneath the hood, Yoopick is a type of combinatorial prediction market where the possible outcomes are the values of the point spread, and each pick is a purchase of a bundle of outcomes in a given interval. We use Hanson’s logarithmic market scoring rules market maker to price the picks — that is, to set the risk/reward ratio. This pricing mechanism also determines the gain or loss when picks are settled early.

Wins and losses on Yoopick are measured in milliyootles, a social currency useful for expressing thanks.

Our market maker can — and we expect will — lose yootles on average. Stated another way, we expect players as a whole to gain on average. At the same time, we actively work to improve our market maker to limit its losses to control inflation in the game.

Because the outcomes of a game are tied together in a unified market, picks in one region automatically affect the price of picks in other regions in a logically consistent way. Players have considerable flexibility in how and what information they can inject into the market. In particular, players can replicate the standard picks like outright winner and spread-adjusted winner if they want, or they can go beyond to pick any interval of the point spread. No matter the form of the pick, all the information flows into a single market that aggregates everything in a unified prediction. In contrast, at venues from Wall Street to Churchill Downs to High Street to Las Vegas Boulevard, markets with many outcomes are usually split into independent one-dimensional markets.

Our goal is to test whether our market design is indeed able to elicit more information than traditional methods. We hope you have fun playing in our Petri dish.

Sharad Goel
David Pennock
Daniel Reeves
Prasenjit Sarkar
Cong Yu

Fred, Fran, and baby makes three

Two mathematicians Fred and Fran were having a baby girl, their first child! They sought the perfect name, a name that would simultaneously reflect togetherness, relationships, and individuality in their burgeoning family. Day and night they debated, rejecting name after name. Finally, they had it! The perfect name!

They named her Erin.

Why?

[Yootleoffer: 1 Yootle for first correct response.]


  • 2008/06/18 Addendum: Fred and Fran both study set theory.
  • 2008/07/27 Addendum: It turns out I didn’t need the 6/18 hint-addendum: commenters had already chimed in with correct answers but, due to a combination of mechanical and pilot error, I didn’t realize it.

    So, … drum roll please…
    the winner is… John! His is the first correct response. Commenter d is also correct with a more succinct and mathematical explanation. Dennis is close but not quite complete. So I’ll award John 2 yootles, d 1 yootle, and Dennis 1/2 yootle. John and d please let me know your contact info to claim your bounty.

    Dennis asks what a yootle is worth. A yootle is a quantified “thanks, I owe you one”. So it’s worth a return favor from me, someone who trusts me, someone who trust someone who trust me, etc.

    Bonus challenge: come up with a family of four with the same property and reasonable names (necessarily of eight letters each).

  • 2008/08/13 Addendum: The bonus round winner is… aj! He hacked up a script and discovered one of apparently many possible “perfectly” named families of four. Details are in the comments of this post. Thanks aj!

Call for Papers and Participation: Workshop on Prediction Markets: Chicago, July 9 2008

I am happy to announce the following prediction market workshop and solicit submissions and participants.


=======================================================================
Call for Contributions and Participation

Third Workshop on Prediction Markets

http://betforgood.com/events/pm2008/index.html

Afternoon of July 9, 2008
Chicago, Illinois

In conjunction with the
ACM Conference on Electronic Commerce (EC’08)

SUBMISSIONS DUE May 23, 2008
=======================================================================

We solicit research contributions, system demonstrations, and
participants for the Third Workshop on Prediction Markets, to be held
in conjunction with the Ninth ACM Conference on Electronic Commerce
(EC’08). The workshop will bring together researchers and
practitioners from a variety of relevant fields, including economics,
finance, computer science, and statistics, in both academia and
industry, to discuss the state of the art today, and the challenges
and prospects for tomorrow in the field of prediction markets.

A prediction market is a financial market designed to elicit a
forecast. For example, suppose a policymaker seeks a forecast of the
likelihood of an avian flu outbreak in 2009. She may float a security
paying $1 if and only if an outbreak actually occurs in 2008, hoping
to attract traders willing to speculate on the outcome. With
sufficient liquidity, traders will converge to a consensus price
reflecting their collective information about the value of the
security, which in this case directly corresponds to the probability
of outbreak. Empirically, prediction markets often yield better
forecasts than other methods across a diverse array of settings.

The past decade has seen a healthy growth in the field, including a
sharp rise in publications and events, and the creation of the Journal
of Prediction Markets. Academic work includes mechanism design,
experimental (laboratory) studies, field studies, and empirical
analyses. In industry, several companies including Eli Lilly, Corning,
HP, Microsoft, and Google have piloted internal prediction
markets. Other companies, including ConsensusPoint, InklingMarkets,
InTrade, and NewsFutures, base their business on providing public
prediction markets, prediction market software solutions, or
consulting services. The growth of the field is reflected and fueled
by a wave of popular press articles and books on the topic, most
prominently Surowiecki’s “The Wisdom of Crowds”.

Workshop topics
===============

The area of prediction markets faces challenges regarding how best
to design, deploy, analyze, implement, and understand prediction
markets. One important research direction is designing mechanisms for
prediction markets, especially for events with a combinatorial outcome
space. Another notable issue is manipulation in prediction
markets. Understanding the effect of manipulation is especially
important for prediction markets to find their way to assist
individuals and organizations in making critical decisions. Moreover,
how to implement market mechanisms that not only are easy to use but
also facilitate information aggregation has been an important problem
for practitioners. Prediction markets face social and political
obstacles including antigambling laws and moral and ethical concerns,
both real and constructed.

Submissions of abstracts for research contributions from a rich set
of empirical, experimental, and theoretical perspectives are
invited. Topics of interest at the workshop include, but are not
limited to:

* Mechanism design
* Game-theoretic analysis of mechanisms, behaviors, and dynamics
* Decision markets
* Combinatorial prediction markets
* Market makers for prediction markets
* Manipulation and prediction markets
* Order matching algorithms
* Computational issues of prediction markets
* Liquidity and thin markets
* Laboratory experiments
* Empirical analysis
* Prediction market modeling
* Industry and field experience
* Simulations
* Policy applications and implications
* Internal corporate applications
* Legal and ethical issues

Submissions of summaries for demonstrations on prediction market
systems are invited. Systems of interest at the workshop include, but
are not limited to:

* Implemented combinatorial prediction markets
* Mature systems and commercial products of market mechanisms
* Research prototypes on prediction markets
* Other collective prediction systems

Submission instructions
=======================

Research contributions should report new (unpublished) research
results or ongoing research. We request an abstract not exceeding one
page for every research contribution.

For system demonstrations, a summary of up to two pages including
technical content to be demonstrated is requested. Please indicate if
the demonstration requires network access.

Research contributions and system demonstrations should be submitted
electronically to the organizing committee at pm2008@umich.edu no
later than midnight Hawaii time May 23, 2008.

At least one author of each accepted research contribution and
system demonstration will be expected to attend and present or
demonstrate their work at the workshop.

Important dates
===============

May 23, 2008: Submissions due midnight Hawaii Time

May 30, 2008: Notification of accepted research contributions and
system demonstrations

July 9, 2008: Workshop date

Organizing committee
====================

Yiling Chen, Yahoo! Inc
David Pennock, Yahoo! Inc
Rahul Sami, University of Michigan
Adam Siegel, Inkling Markets

More information
================

For more information or questions, visit the workshop website:
http://betforgood.com/events/pm2008/index.html

or email the organizing committee: pm2008@umich.edu

Call for Papers and Participation: Workshop on Ad Auctions: Chicago, July 8-9 2008

I am happy to announce the following ad auctions workshop and solicit submissions and participants.


=======================================================================
Call for Papers

Fourth Workshop on Ad Auctions
http://research.yahoo.com/workshops/ad-auctions-2008/

July 8-9, 2008
Chicago, Illinois, USA

SUBMISSIONS DUE MAY 11, 2008

In conjunction with the
ACM Conference on Electronic Commerce (EC’08)
=======================================================================

We solicit submissions for the Fourth Workshop on Ad Auctions, to be
held July 8-9, 2008 in Chicago in conjunction with the ACM Conference
on Electronic Commerce. The workshop will bring together researchers
and practitioners from academia and industry to discuss the latest
developments in advertisement auctions and exchanges.

In the past decade we’ve seen a rapid trend toward automation in
advertising, not only in how ads are delivered and measured, but also
in how ads are sold. Web search advertising has led the way, selling
space on search results pages for particular queries in continuous,
dynamic “next price” auctions worth billions of dollars annually.

Now auctions and exchanges for all types of online advertising —
including banner and video ads — are commonplace, run by startups and
Internet giants alike. An ecosystem of third party agencies has grown
to help marketers manage their increasingly complex campaigns.

The rapid emergence of new modes for selling and delivering ads is
fertile ground for research from both economic and computational
perspectives. What auction or exchange mechanisms increase advertiser
value or publisher revenue? What user and content attributes
contribute to variation in advertiser value? What constraints on
supply and budget make sense? How should advertisers and publishers
bid? How can both publishers and advertisers incorporate learning and
optimization, including balancing exploration and exploitation? How do
practical constraints like real-time delivery impact design? How is
automation changing the advertising industry? How will ad auctions and
exchanges evolve in the next decade? How should they evolve?

Papers from a rich set of empirical, experimental, and theoretical
perspectives are invited. Topics of interest for the workshop include
but are not limited to:

* Web search advertising (sponsored search)
* Banner advertising
* Ad networks, ad exchanges
* Comparison shopping
* Mechanism and market design for advertising
* Ad targeting and personalization
* Learning, optimization, and explore/exploit tradeoffs in ad placement
* Ranking and placement of ads
* Computational and cognitive constraints
* Game-theoretic analysis of mechanisms, behaviors, and dynamics
* Matching algorithms: exact and inexact match
* Equilibrium characterizations
* Simulations
* Laboratory experiments
* Empirical characterizations
* Advertiser signaling, collusion
* Pay for impression, click, and conversion; conversion tracking
* Campaign optimization; bidding agents; search engine marketing (SEM)
* Local (geographic) advertising
* Contextual advertising (e.g., Google AdSense)
* User satisfaction/defection
* User incentives and rewards
* Affiliate model
* Click fraud detection, measurement, and prevention
* Price time series analysis
* Multiattribute and expressive auctions
* Bidding languages for advertising

We solicit contributions of two types: (1) research contributions,
and (2) position statements. Research contributions should report new
(unpublished) research results or ongoing research. The workshop
proceedings can be considered non-archival, meaning contributors are
free to publish their results later in archival journals or
conferences. Research contributions can be up to ten pages long, in
double-column ACM SIG proceedings format:
http://www.acm.org/sigs/publications/proceedings-templates
Position statements are short descriptions of the authors’ view of how
ad auction research or practice will or should evolve. Position
statements should be no more than five pages long. Panel discussion
proposals and invited speaker suggestions are also welcome.

The workshop will include a significant portion of invited
presentations along with presentations on accepted research
contributions. There will be time for both organized and open
discussion. Registration will be open to all EC’08 attendees.

The first three workshops on sponsored search auctions successfully
attracted a wide audience from academia and industry working on
various aspects of web search advertising. Following the footsteps of
the previous workshops, the Fourth Workshop on Ad Auctions strives to
be a venue that helps address challenges in the broader field of
online advertising, by providing opportunities for researchers and
practitioners to interact with each other, stake out positions, and
present their latest research findings. While the first three
workshops focused on web search advertising, we have broadened the
scope this year to include auctions and exchanges for any form of
online advertising.

Submission Instructions
=======================

Research contributions should report new (unpublished) research
results or ongoing research. The workshop’s proceedings can be
considered non-archival, meaning contributors are free to publish
their results later in archival journals or conferences. Research
contributions can be up to ten pages long, in double-column ACM SIG
proceedings format:
http://www.acm.org/sigs/publications/proceedings-templates
Positions papers and panel discussion proposals are also welcome.

Papers should be submitted electronically using the conference
management system:
http://www.easychair.org/conferences/?conf=adauctions2008
no later than midnight Hawaii time, May 11, 2008. Authors should also
email the organizing committee ( adauctions2008@yahoogroups.com ) to
indicate that they have submitted a paper to the system.

At least one author of each accepted paper will be expected to attend
and present their findings at the workshop.

Important Dates
===============

May 11, 2008 Submissions due midnight Hawaii time
a. Submit to:
http://www.easychair.org/conferences/?conf=adauctions2008
b. Notify adauctions2008@yahoogroups.com
May 23, 2008 Notification of accepted papers
June 8, 2008 Final copy due

Organizing Committee
====================

Susan Athey, Harvard University
Rica Gonen, Yahoo!
Jason Hartline, Northwestern University
Aranyak Mehta, Google
David Pennock, Yahoo!
Siva Viswanathan, University of Maryland

Program Committee
=================

Gagan Aggarwal, Google
Animesh Animesh, McGill University
Moshe Babaioff, Microsoft
Tilman Borgers, University of Michigan
Max Chickering, Microsoft
Chris Dellarocas, University of Maryland
Ben Edelman, Harvard University
Jon Feldman, Google
Jane Feng, University of Florida
Slava Galperin, A9
Anindya Ghose, New York University
Kartik Hosanagar, University of Pennsylvania
Kamal Jain, Microsoft
Jim Jansen, University of Pennsylvainia
Sebastien Lahaie, Yahoo!
John O. Ledyard, Caltech
Ying Li, Microsoft
Ilya Lipkind, A9
Preston McAfee, Yahoo!
Chris Meek, Microsoft
John Morgan, University of California Berkeley
Michael Ostrovsky, Stanford University
Abhishek Pani, Efficient Frontier
Martin Pesendorfer, London School of Economics
David Reiley, Yahoo!
Tim Roughgarden, Stanford University
Catherine Tucker, Massachusetts Institute of Technology
Rakesh Vohra, Northwestern University

More Information
================

For more information or questions, visit the workshop website:
http://research.yahoo.com/workshops/ad-auctions-2008/

or email the organizing committee:
adauctions2008@yahoogroups.com

A historic MayDay: The US government’s call for help on regulating prediction markets

May 1, 2008 could signal a turning point for the prediction markets industry.*

Yesterday, the US Commodity Futures Trading Commission (CFTC) issued a request for public comments as they mull over the legal and regulatory status of prediction markets.

I read the Concept Release in detail, and I am happy to report that it is a careful, thoughtful, even scholarly document that reflects a solid understanding of the goals of prediction markets, and that appears to signal a real willingness on the part of the CFTC to consider reasonable options and arguments.

In short, this development leaves the optimist in me dreaming of a day in the not so distant future when US companies can try out some truly innovative products.

It’s not often that an industry in its infancy cries out for more government oversight. But the CFTC is certainly preferable to the gambling Gestapo.

Anyone who desires to see more prediction markets in the US, please let the CFTC know what you think!


*Or not.