-

On Wednesday, January 30, 2008, at 9:00 AM PST (12:00 PM EST; 5:00 PM GMT; 6:00 PM CET), dollar-thirsty Nigel Eccles (pictured above) will be introducing HubDub at DEMO 2008 (one of the best IT conferences, along with eTech, LeWeb, CES, etc.). The DEMO website will be live-streaming the presentation video.

My best wishes go to Nigel Eccles for his presentation. (Is there something to win, at that DEMO conference? Is it a startup contest? Is there a trophy to win, at the end?)

In my view, the launch of HubDub (both a news aggregator and a MSR-powered, play-money prediction exchange) is a milestone.

It’s not the first time that a prediction exchange adds content to its offerings (they all do that, now, even in small ways), but it’s the first time that:

1. Quality content from the outside (that is, from professional media organizations, including news blogs) is systematically included into the exchange offerings;
2. Pertinent associations between the prediction markets and the news stories are proposed. (On top of the news aggregation mechanism, people vote for the most relevant stories on each prediction market page, so as to help the other traders to be better informed on the topic at hand. And, when creating an event derivative, the manager is asked to jot down keywords, which will be used by the search engine to harness links related to that prediction market.)

The Midas Oracle readers remember that I have been bullish on HubDub since day one. (See my previous post: HubDub wil redefine the play-money exchange landscape.) Others are now following.

I’m not alone, anymore, in thinking that prediction market pages should published the URLs of the related advanced indicators (i.e., primary sources of information).

Enterprise prediction market consultant Jed Christiansen (pictured above).

Internet usability expert Alex Kirtland (pictured above).

And, after a good discussion, others came in agreement with the no-brainer idea that more external links and more information can be good for the prediction markets. (Next obvious discoveries: The sky is blue; The sun rises from the East; Water is wet; War is bad; The Internet is world wide; The French fries are not fried in France; The French bread is not baked in France; etc. )

If you think of it, David Pennock (pictured above) is the man to hire to tackle the problematic of integrating news links/stories with prediction markets —since he is a world-renowned expert in both microeconomics and search engine technology. We are on his turf, here. Hence, he should be the one leading us —as opposed to us pulling him.

What should the humans do with the prediction markets? As Michael Giberson knows better than I do, probabilistic predictions are the offspring of the trading activities on the event derivative markets. At inception, BetFair and TradeSports didn’t give the first fig about those probabilistic predictions, but today, the event derivative industry is being defined both by its betting side and its forecasting side.

And now we can see the main difference between the betting exchange approach and the prediction market approach: promoting (the trading of low-cost event derivatives) to bettors versus promoting (the generating of dynamic, objective probabilistic predictions) to people.

See, the prediction market approach consists in chasing people with news and probabilities. Hence, my personal version of HubDub would feature an aggregation news item (a la TechMeme, Memeorandum, or BallBug), mixed up with the appropriate InTrade/TradeSports/BetFair dynamic chart to give a hint on how the issue at hand will be settled in the near future. Content, first, and then the related prediction market chart —as an informative appendix to a good scoop or quality analysis. The prediction market page would anti-chronologically list all the relevant news links.

And since the US (not Scotland) is the most fertile place for web search technologies, I bet that we will see soon some US-based HubDub-inspired startups popping up like champagne bubbles in the coming months and years.

Better Prediction Markets = A Better World

In other words, how could you make Justin Wolfers’ prediction market analysis visually coupled with the prediction market chart he comments on?

Alex Kirtland, back to you.

URLs, please.

…asks Slate’s Daniel Gross —via Mister Usability (Alex Kirtland), who needs to go and get his own gravatar.

So, I’ve been watching the action in one of the political futures markets this evening, Intrade. And the action in this prediction market has reinforced my opinion that these are less futures markets than immediate-past markets. The price movement tends to respond to conventional wisdom and polling data; it doesn’t lead them.

Throughout the day and into the early evening, while polls were still open, Democratic investors, mimicking the post-Iowa c.w. and polls, believed Obama was highly likely to be the Democratic nominee. The Obama contract was trading in the lows 70s, meaning investors believed he had a 70 percent chance of being the nominee, while Hillary Clinton contracts were in the 20s. [...] At 6 p.m., this market had written Hillary Clinton’s entire presidential campaign off. At 9:30 p.m., it was calling a dead heat. What caused investors to change their minds so drastically in the space of a couple of hours? A few data points that went against the day’s prevailing conventional wisdom and polls. [...]

See also Niall O’Connor’s assessment:

I am looking forward to the post New Hampshire Caucus, when all you prediction market advocates crawl out from under your stones. For the record at one point the market on Intrade and Betfair was suggesting that Obama had a 95% probability of winning the caucas; whilst Intrade had him at 77% to win the nomination.A case perhaps of both the foolery of crowds and, the market biting back.

New Hampshire will go down as the Black Wednesday of prediction markets and unless there is now objective transparent debate (as opposed to the usual biased sabre rattling) – prediction markets will be dead in the water.

My answer to Dan Gross’ legitimate question and to Niall O’Connor’s snarky comment:

1. Prediction markets are forecasting tools of convenience that feed on advanced indicators. When those advanced indicators are wrong, the prediction markets are wrong.
2. If you prefer the polls or the pundits, your call —but polls and pundits were also wrong, this time, right? Required reading for mister Niall O’Connor: “New Hampshire’s Polling Fiasco” + “Analysis: pundits eat crow“.
3. The ultimate forecasting tool would be a way to reverse our psychological arrow of time —so as to remember the future instead of the past. Only science-fiction writers and some imbécile ( ) believe in that.
4. The prediction market approach is to stick with the markets, on the long term. Take their successes. Take their failures. Unlike Donald Luskin and Markos Moulitsas, Chris Masse will not turn against the prediction markets when they fail punctually. What counts is the long series.
5. My first point should be included in the prediction markets approach definition, in my view, but others (like economist Michael Giberson) might have different opinions.
6. With respect to my first point, I bet that the prediction markets will never replace the polls as the forecasting tool of choice for political analysts —on that particular point (but not on a myriad of others), I break away from Justin Wolfers’ irrational exuberance and I side with Emile Servan-Schreiber of NewsFutures (my preferred play-money prediction exchange). Prediction market reporting will have a function, indeed (as suggests Justin Wolfers), but not the dominant function.
7. Going forward, prediction market journalism should emphasize relative accuracy (as opposed to absolute accuracy) —that is, comparing prediction markets with polls and pundits, which is what Robin Hanson has said from day one. Our good friend Niall O’Connor has difficulty to compute that, apparently. He should eat more fish.

—

Justin Wolfers:

“In a few years, we may regard the second half of the 20th century as the aberration in which the press used polls rather than markets to track political races,” Justin Wolfers, a business professor at the University of Pennsylvania’s Wharton School, wrote in an e-mail message. “And in the 21st century, we may return to the habits of the early 20th century, reporting on political races through the lens of prediction markets rather than polls.”

Emile Servan-Scheiber:

1) The traders themselves are the first to look at the polls to inform their trades. So the polls are here to stay.

2) Our recent experience in Western Europe seems to indicate that the superior accuracy of markets over polls when predicting elections may be a U.S. artifact that isn’t so easily reproducible elsewhere. I’ve discussed this with Forrest Nelson of IEM [Iowa Electronic Markets], and apparently, ever since the Truman-Dewey polling debacle of 1948, U.S. pollsters have adopted a policy of reporting mostly raw numbers rather than projections based on sophisticated secret formulas, so they can’t be accused of manipulating opinion. However, raw numbers are notoriously unreliable when based on small samples, and Western European pollsters never report them, preferring instead to publish projections based on historically-informed statistical formulas. What we’ve observed in France and Holland is that it it’s very hard to beat the accuracy of such projections.

[I don't make mine Emile Servan-Schreiber's second point, but that's a minor.]

—

InTrade’s expired prediction markets:

—

New Hampshire

—

The Democrats

—

The Hillary Clinton event derivative was expired to 100.

—

The Republicans

—

The John McCain event derivative was expired to 100.

—

Iowa

—

The Democrats.

The Barack Obama event derivative was expired to 100.

—

The Republicans

The Mike Huckabee event derivative was expired to 100.

—

Source: InTrade

—

[A more complete prediction market reporting should have included expired contracts from NewsFutures and BetFair. Sorry for that. Note that InTrade-TradeSports is the only exchange to offer a "closed contacts" section.]

—

NEXT: Prediction Markets 101 + Who did best in explaining the prediction markets to the lynching crowd? + After the New Hampshire fiasco, 16 people came to defend the prediction markets, so far. + The prediction markets deserve a fair trial. + Prediction Markets = the greatest time-saving invention of this century

—

This is, quite frankly, some of the worst interaction design I’ve ever seen.

Photo: Alan Lewis

Alex Kirtland: Finally, Meg Whitman recently talked about how important improving the eBay user experience is to success of eBay. How has that had an impact on the culture / work style of eBay’s development teams?

Alan Lewis: This shift has been in motion for many years, actually. For a long time at eBay, the biggest problem was scale. Much of the engineering effort and time spent developing the website would go into things that the user would never see. We got better and better at keeping the site up, and we got to a place where we were more confident in our ability to handle the continued growth. So a few years back we started to put a much higher priority on improving the user experience, which we all knew was in need of improvement.

The reorganization that was done at the beginning of 2007 was by no means the first step – as I said the company as a whole recognized the problem long before that. The executives, I think, realized that the company had to be structured differently to tackle the user experience improvements that were needed.

As somebody “in the trenches” here at eBay I have been very pleased with how the culture has shifted. People are willing to take more risks now. When I propose doing something, it is rare that I hear someone saying “no, that’ll never work,” but instead they will say “ok, let’s try that out and see what we can learn from it.”

A message that our prediction exchanges and prediction software vendors should listen to.

Robin Hanson will be presenting on prediction markets at the Money Tech conference. He is not yet on the official program, but our friend (and prediction market skeptic) Barry Ritholtz tells us that Robin Hanson was at the pre-conference dinner. (Robin Hanson was quite surprisingly “fascinating”, he wrote. Will Robin Hanson manage to turn this skeptic into a fanboy? We’ll see.)

Psstt… Barry Ritholtz talks about November 2007 while the official site says February 2008. Bizarre.

Thanks to Alex Kirtland for alerting us about this Money Tech conference, last month.

UPDATE: Barry Ritholtz comments…

November? How did that happen?

I meant February.

My current excuse for any brain glitch like this is to declare that I smoked way too much pot in college and leave it at that. (That’s much better than admitting advanced senility/aging)

“cash” in green, “contracts” in blue, and “net worth” in black

Alex Kirtland, if you’re still alive, how would you improve the usability of this chart? Thicker lines??

—

© NewsFutures

—

UPDATE: Alex…

Um, I’d give both charts titles, to start.

The Crowd IQ people are friendly and open minded, as far as I can tell, having interacted with them only twice, by e-mail. I hope they will find a way to come back to the field of prediction markets. I think they blamed their failure on market design —lack of automated market maker or lack of MSR, I don’t remember well.