The main EC’11 conference includes talks on prediction markets, crowdsourcing, auctions, game theory, finance, lending, and advertising. The papers span a spectrum from theoretical to applied. If you want evidence of the latter, look no further than the roster of corporate sponsors: eBay, Facebook, Google, Microsoft, and Yahoo!.

There are also a number of interesting workshops and tutorials in conjunction with EC’11 this year, including:

Workshops:

• 7th Ad Auction Workshop
• Workshop on Bayesian Mechanism Design
• Workshop on Social Computing and User Generated Content
• 6th Workshop on Economics of Networks, Systems, and Computation
• Workshop on Implementation Theory

Tutorials:

• Bayesian Mechanism Design
• Conducting Behavioral Research Using Amazon’s Mechanical Turk
• Matching and Market Design
• Outside Options in Mechanism Design
• Measuring Online Advertising Effectiveness

The umbrella FCRC conference includes talks by 2011 Turing Award winner Leslie G. Valiant, IBM Watson creator David A. Ferrucci, and CMU professor, CAPTCHA co-inventor, and Games With a Purpose founder Luis von Ahn.

Hope to see many of you there!

Back to the device. It’s pretty awesome. It’s a Windows tablet computer with Cantor’s custom software — pretty well designed considering this is a financial firm. You can bet on the winner, against the spread, or on one-off propositions like whether the offensive team in an NFL game will get a first down, or whether the current drive will end with a punt, touchdown, field goal, or turnover. The interface is pretty nice. You select the type of bet you want, see the current odds, and choose how much you want to bet from a menu of common options: $5, $10, $50, etc. You can’t bet during certain moments in the game, like right before and during a play in football. When I was there only one game was available for in-running betting. Still, it’s instantly gratifying and — I hate to use this word — addictive. Once my friend saw the device in action, he instantly said “I’m getting one of those”.

When I first heard of Cantor’s foray into sports betting, I assumed they would build “betfair indoors”, meaning an exchange that simply matches bettors with each other and takes no risk of its own. I was wrong. Cantor’s mechanism is pretty clearly an intelligent automated market maker that mixes prior knowledge and market forces, much like my own beloved Predictalot minus the combinatorial aspect. Together with their claim to welcome sharps, employing a market maker means that Cantor is taking a serious risk that no one will outperform their prior “too much”, but the end result is a highly usable and impressively fun application. Kudos to Cantor.

Predictalot v0.3 is easier to play. We whittled down the ‘Make Prediction’ process from four steps to just two. Even if you don’t want to wager, with one click come check out the projected odds of nearly any crazy eventuality you can dream up.

Please connect to facebook and/or twitter to share your prediction prowess with your friends and followers. You’ll earn bonus points and my eternal gratitude.

The odds start off at our own prior estimate based on seeds and (new this year) the current scores of ongoing games, but ultimately settle to values set by “the crowd” — that means you — as predictions are bought and sold.

For the math geeks, Predictalot is a combinatorial prediction market with over 9 quintillion outcomes. Prices are computed using an importance sampling approximation of a #P-hard problem.

What kind of information can we collect that a standard prediction market cannot? A standard market will say that Texas A&M is unlikely to win the tournament. Our market can say more. Yes, A&M is unlikely to reach the Final Four and even more unlikely to win apriori, but given that they somehow make it to the semifinals in Houston, less than a two hour drive from A&M’s campus, their relative odds may increase due to a home court advantage.

Here’s another advantage of the combinatorial setup. A standard bookmaker would never dare to offer the same millions of bets as Predictalot — they would face nearly unlimited possible losses because, by tradition, each bet is managed independently. By combining every bet into a single unified marketplace, we are able to limit the worst-case (virtual) loss of our market maker to a known fixed constant.

I’ve been considering submitting some thing(s): I’m curious if anyone else is planning to submit or attend?

Date: 3 – 5 April 2011
Event: Third International Conference on Prediction and Information Markets
Location: Nottingham Conference Centre
Organiser: Nottingham Business School

Details:

The Third International Conference on Prediction and Information Markets will be held in association with Economic Issues and the Journal of Prediction Markets.

Prediction / information markets offer a way of harnessing the wisdom of crowds. They have been used to aggregate information in order to provide forecasts of a wide range of events…

In recent years, a number of companies have employed these markets as a means of aggregating the information dispersed widely among their employees and customers…

Call for papers and presentations
Please send an abstract (maximum of 200 words) to Professor Leighton Vaughan Williams by email, by the closing date for receipt of abstracts of Monday 21 February 2011. Confirmation of receipt of abstracts will be sent within a maximum of five working days.

I’m thrilled to report that Predictalot had an Indian makeover, launching as Predictopus* for the ICC Cricket World Cup. The Yahoo! India team did an incredible job, leveraging the idea and some of the code base of Predictalot, yet making it their own. Predictopus is not a YAP — it lives right on the Yahoo! Cricket website, the official homepage for the ICC Cricket World Cup. They’re also giving away Rs 10 lakhs — or about $22,000 if my calculations are correct — in prizes. Everything is bigger in India, including the crowds and the wisdom thereof. It will be great to see the game played out on a scale that dwarfs our college basketball silliness in the US.

The Y! India team reused some of the backend code but redid the frontend almost entirely. To adapt the game to cricket, among other chores, we had to modify our simulation code to estimate the starting probabilities that any team would win against any other team, even in the middle of a game. (How likely is it for India to come back at home from down 100 runs with 10 overs left and 5 wickets lost? About 25%, we think.) These starting probabilities are then refined further by the game-playing crowds.

It’s great to see an experiment from Labs grow into a full-fledged product run by a real product team in Yahoo!, a prime example of technology transfer at its best. In the meantime, we (Labs) are still gunning for a relaunch of Predictalot itself for March Madness 2011, the second year in a row. Stay tuned.

2011/02/24 Update: An eye-catching India-wide ad campaign for predictopus is live, including homepage, finance, movies, OMG, answers, mail, everywhere! Oh, and one of the prizes is a Hyundai.

In the eyes of a casino, a sharp is indistinguishable from a cheat. More than boring, this seems fundamentally unfair and unsustainable, inviting disguise. It also turns off a wealthy, influential, and game-loving segment of the population.

What I want: A casino by geeks for geeks that celebrates innovation, encourages cleverness, welcomes gadgets and wifi, and fosters hacking, outwit, and outplay.

At least one casino has seen the light. The M Casino in Las Vegas is parterning with Cantor Fitzgerald to support in-game sports betting with few rules and caps, inviting sharps to, more or less, “bring it on”.

…gamblers can bet on the game even during play, accepting ever-changing point-spreads and odds. They can invest money on a Knicks foul shot going through the hoop or a Dodger getting to first base — contending with ever-evolving odds.

More critically, bettors can create hedges while jumping in and out of positions. But instead of buying into the fast-breaking moves of Microsoft, they’re betting on the Mariners’ impending fortunes.

This form of wagering is new to Las Vegas but old-hat in other markets.

…unlike in most other casinos, laptop computers are welcome.

…”The M wants [sharp bettors] to be there,” believes [professional sports-bettor Steve] Fezzik. “They want your information, and that’s a progressive attitude.”

Kudos to M for taking a chance on a more interesting future and to Cantor for making it happen.

What Cantor is debuting may not be a whole lot more than betfair indoors, but it’s a long overdue start. Here’s to hoping we see even more innovation, including smarter and more expressive markets.

More people are playing Predictalot today than Mafia Wars or Zynga Poker… On Yahoo!, that is.

In fact, Predictalot is the #1 game app on Yahoo! Apps by daily count. By monthly count, we are 5th and rising.

A prediction is being made about every three minutes.

Come join the fun.

Yahoo! Lab’s own Predictalot market is now live and waiting for you to place almost any prediction your heart desires about the World Cup in South Africa.

Here are some terribly useful things you can learn this time around. All numbers are subject to change, and that’s kind of the point:

• There’s a 37% chance Brazil and Spain will both make it to the final game; there’s only a 15% chance that neither of them will make it
• There’s is a 1 in 25 chance Portugal will win the cup; 1 in 50 for Argentina
• 42.92% chance that a country that has never won before will win
• 19.07% chance that Australia will advance further than England
• 65.71% chance that Denmark, Italy, Mexico and United States all will not advance to Semifinals
• Follow Predictalot on twitter for more

If you think these odds are wrong, place your virtual wager and earn some intangible bragging rights. You can sell your prediction any time for points, even in the middle of a match, just like the stock market.

There are millions of predictions available, yet I really believe ours is the simplest prediction market interface to date. (Do you disagree, Leslie?) We have an excellent conversion rate, or percent of people who visit the site who go on to place at least one prediction — for March Madness, that rate was about 1 in 5. One of our main goals was to hide the underlying complexity and make the app fast, easy, and fun to use. I personally am thrilled with the result, but please go judge for yourself and tell us what you think.

In the first version of Predictalot, people went well beyond picking the obvious like who will win. For example, they created almost 4,000 “three-dimensional” predictions that compared one team against two others, like “Butler will advance further than Kentucky and Purdue”.

If you’re not sure what to predict, you can now check out the streaming updates of what other people are predicting in your social circle and around the world:

Also new this time, you can join a group and challenge your friends. You can track how you stack up in each of your groups and across the globe. We now provide live match updates right within the app for your convenience.

If you have the Yahoo! Toolbar (if not, try the World Cup toolbar), you can play Predictalot directly from the toolbar without leaving the webpage you’re on, even if it’s Google.

Bringing Predictalot to life has been a truly interdisciplinary effort. On our team we have computer scientists and economists to work out the market math, and engineers to turn those equations into something real that is fast and easy to use. Predictalot is built on the Yahoo! Application Platform, an invaluable service (open to any developer) that makes it easy to make engaging and social apps for a huge audience with built-in distribution. And we owe a great deal to promotion from well-established Yahoo! properties like Fantasy Sports and Games.

We’re excited about this second iteration of Predictalot and hope you join us as the matches continue in South Africa. We invite everyone to join, though please do keep in mind that the game is in beta, or experimental, mode. (If you prefer a more polished experience, check out the official Yahoo! Fantasy Sports World Soccer game.) We hope it’s both fun to play and helps us learn something scientifically interesting.

Read more here, here, and here.

Or watch a screencast of how to play:

Buy one house at the beach and a second house near a ski resort. You live in the beach house in the winter and the ski resort in the summer. You rent out the beach house in the summer and the ski resort in the winter.* Can your earnings (rental revenue minus mortgage costs) be enough to live on?

Why it could work: the cost of each house will be roughly proportional to the average annual rental income in that location. If you didn’t live in the properties at all, you should roughly break even (income = mortgage payments). But you are living in each location during the time when rent is essentially free (not contributing to the average) so you have no housing costs. If you find good enough deals (or put money down, or have some small income like freelance writing, etc.) your income may exceed your mortgage enough to live on.

What’s the minimum you could get started with on this strategy? Probably a minimum income to live comfortably as a starting point would be $70K before taxes: see justification below. Assume you can make about 5% of a home’s value in rental income: this seems feasible. Then you need $1.4 million invested in real estate (say two $700K houses) with no mortgage (completely paid). Suppose you can also borrow at 5%. Then if you put 50% down on two $1.4 million properties ($2.8 million total), your effective mortgage rate is 2.5% and your “spread” is 2.5%, so you again earn $70K, but now you have two twice as nice houses (but more risk, need to qualify for loan, etc.). Now here is some magic. Suppose you find an incredible deal (say, in a down real estate market) and you can earn 10% in rental income. You can borrow at 5% and only want to put 20% down, still a respectable portion that the bank may be willing to go for. You buy two $600K homes ($1.2 million total) needing only $240K in cash. Now your rental revenue is $120K and your mortgage payments are $48K, so your net income is, viola, $72K!

Didn’t I forget about taxes and insurance? No, I’m just assuming these can be covered by your $70K income. I did forget about health insurance, though: that could threaten the strategy, at least in the United States. You can can hope that the new health care law helps, or keep an enjoyable day job, or purchase insurance out of the $70K.

You might say $70K pretax is not enough to live the lifestyle you want. But remember, you effectively have no housing costs, and this is just meant as a starting point. This is your “muse” as Tim Ferriss calls it: a steady reliable income that is your buffer. You still should pursue freelance ideas or business ideas that you are passionate about, and one of those just might hit it big. This just gives you freedom to pursue other ideas on your own. Hopefully even at $70K you can save some money to purchase additional properties and increase your income. Note that once your mortgage is paid off, your income will go up.

One nice thing about this strategy, and real estate investments in general, is that they are naturally inflation adjusted: rental rates should go up if inflation goes up.

This really only seems practical for people without kids in school. Although I suppose if your kids went to school in the beach location it might work. You’d only spend 2.5 months in the ski resort.

Certainly there are downsides: constantly moving, living in off-season tourist towns, living in properties that are rented half the year, dealing with renters, risk of loss or default, and managing the business headaches.

If housing arbitrage could really work, why aren’t more people doing it? Maybe it requires too much capital and maybe my math is wildly optimistic. Probably it’s no more than a fun mental exercise. I’m sure it’s been thought of. I can’t find it on a cursory web search but it seems hard to articulate to a search engine. If enough people started doing it, by definition house prices would go up to eliminate the arbitrage.

__________
* Maybe take a week or two in the summer at the beach and the winter at the ski house.

It turns out that a Laplace distribution is a pretty good model of the stock market. The Laplace distribution is parametrized by its median u and its average absolute difference from median b. I computed these two parameters for the S&P 500 data and plugged them into a Laplace distribution in Mathematica, then used that to generate 59 years worth of random simulated S&P 500 prices. Here is the resulting histogram.

This is not a best fit: this is simply the same u and b computed on the data and then plugged into the distribution. Here are the two histograms on top of each other.

At the aggregate level the stock market is well behaved: it’s randomness is remarkably predictable. It’s amazing that this social construct — created by people for people, and itself often personified — behaves so much like a physical process, more so than any other man-made entity I can think of.

The graphs also hint at the futility of attaching reasons to price movements every single day. Today, “the prospects for continued low borrowing costs buoyed investors’ hopes for the U.S. economy”. Tomorrow, there may be “profit taking”.** Why do reporters feel obligated to explain why, or more to the point why do readers demand to be told? Why must we infer reasons, see momentum where there may be none, and assign labels like bull and bear? Why can’t we accept randomness?***

Update: Anthony Towns conducted a fascinating and puzzling follow-up analysis showing that the volatility of the stock market has been going up steadily over the years, even though the mean return has not.
__________
* The log difference is the log of the price on day d minus the log of the price on day d-1, or equivalently ln(d/(d-1)).
** I’d love to see a controlled experiment where financial reporters are given randomized reports about the Dow and watch them manufacture explanations, I imagine occasionally invoking the same cause for both ups and downs… (a) The prospect of higher interest rates spooked investors today; or (b) the Fed’s willingness to raise rates signals a recovering economy — investors rejoiced.
*** Let me clarify. The efficient market hypothesis implies both randomness and rationality: Randomness in the sense of statistical independence (no momentum), and rationality in the sense that price changes reflect new information. So I’m not saying that prices change for no reason, just that there is rarely an easily-stated single explanation for the overall market. (BTW, “profit taking” is never a valid explanation under EMH.)