Victory of the mind over matter!!!!!!

The PopSci PPX prediction exchange has finally created a jatropha biofuel prediction market, as the Freakonomics blog was suggesting them to do.

[…] some Goldman Sachs data on the estimated cost per barrel of fuel made from a variety of sources:

Cellulose: $305
Wheat: $125
Rapeseed: $125
Soybean: $122
Sugar Beets: $100
Corn: $83
Sugar Cane: $45
Jatropha: $43

Now, the second part of the equation is to promote this new prediction market, so it gets traded and a running-time probabilistic prediction is generated. (The interaction between a blog audience and a prediction market is part of my concept of X group. I&#8217-m bullish on that.)

Next: Freakonomics + PopSci PPX = Not yet an X group + THE FREAKONOMICS BLOG AND THE JATROPHA PREDICTION MARKET AT POPSCI PPX NOW FORM AN X GROUP.

Previous blog posts by Chris F. Masse:

• The CFTC is going to close the comments in 9 days. We have 9 days left to convince the CFTC to accept FOR-PROFIT prediction exchanges (e.g., InTrade USA or BetFair USA), and counter the puritan and sterile petition organized by the American Enterprise Institute (which has on its payroll Paul Wolfowitz, the bright masterminder of the Iraq war).
• Forrest Nelson valids Emile Servan-Schreiber.
• Averaging One’s Guesses
• Americans love rankings, but Americans hate to be assessed subjectively.
• A libertarian view on the Internet betting and gambling industry in the United States of America
• The CFTC is going to close the comments in 10 days. We have 10 days left to convince the CFTC to accept FOR-PROFIT prediction exchanges (e.g., InTrade USA or BetFair USA), and counter the puritan and sterile petition organized by the American Enterprise Institute (which has on its payroll Paul Wolfowitz, the bright masterminder of the Iraq war).
• The Numbers Guy

King Abdullah of Saudi Arabia has said he does not want to go down in history as Mr. Bush’s Arab Tony Blair.

New York Times

Awad Awad/Agence France-Presse — Getty Images
King Abdullah of Saudi Arabia in Riyadh in March, during a meeting of Arab heads of state in which he called the United States presence in Iraq “an illegal foreign occupation,” infuriating the White House.

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Saudi Arabia prediction markets, anyone??

Thanks, but No Thanks. Difficult to get info. Saudi Arabia is like a giant cult, with a two-tier population &#8212-the people, and the rulers (the multi-married &#8220-princes&#8221-, who proliferate like rabbits).

That&#8217-s why I think Robin Hanson made an error when he picked up the Middle East as the geopolitical target of his DARPA&#8217-s Policy Analysis Market. Mid-East politics is too arcane for us, Westerners. And the whole Iraq war mess shows you that the Americans, in particular, don&#8217-t get the Arabo-Muslim world.

Would Mid-East prediction markets with strong incentives and high participation improve our intelligence??? Yes, in theory. But, as we have seen on Midas Oracle in the past weeks, the scholars have great ideas for brand-new event derivatives, but&#8230- as I&#8217-m used to ask&#8230- how many divisions??? They have no traction.

The field of prediction markets is where great ideas meet their coffin. The emphasis is put on a bunch of aloof scholars just because they can use a scientific calculator. We need thinkers/managers who both can make us dream with socially relevant event derivatives and understand the practicalities of the prediction markets.

&#8230- would be an interesting idea &#8212-Eric Zitzevitz would probably agree.

Addendum (January 2, 2006): Yahoo! Tech Buzz Game has one Sirius &amp- XM prediction market, says David Pennock in the comment area.

There&#8217-s a set of Robin Hanson slides that are much more interesting than the presentation he gave at Yahoo! Confab.

– It&#8217-s bigger (67 slides vs. 21) and it covers the prediction market problematic in a more comprehensive way (including MSR).

– The decision market concept takes a minor place, whereas at Confab, Robin Hanson made the mistake to focus most of his speech on it &#8212-interesting concept but that was the wrong audience (Confab attendees wanted specific answers about basic prediction market questions).

– Here are excerpts, but I recommend you to download the presentation file, read it from A to Z, and share it with your friends and colleagues. (And if you had downloaded his Confab slides, direction the trash can of your computer &#8211-don&#8217-t keep 7 megas of useless bits of information.)

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Prediction Markets for Science? – (PPT) – by Robin Hanson – 2006-12-XX

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Today’s Science Prices (Play $ Alas) – [Foresight Exchange]
11-14% P != NP proven by 2010
16-18% Cancer cured by 2010
16-19% Cold fusion works by 2015
28-29% Mammal immortality by 2015
28-31% Eventual universe collapse
68-70% Fusion energy sold by 2045
74-76% Extraterrestrial life by 2050
91-95% A gamma ray burst w/in 33Mly
93-95% Cosmo constant &gt- 0
93-96% Neutrino mass &gt- 0

Science Decision Markets
E[ Iraq civil war | US moves troops out? ]
E[ Sea levels | Raise CO2 tax ]
E[ Lifespan | Health care reform ]
E[ Murders | More gun control ]
E[ Cancer deaths | More research funding ]
E[ Firm stock price | fire CEO? ]
E[ Succeed? | Fund project ]
E[ Publications | Hire candidate ]
E[ Citations | Publish ]

Theory I – Old
“Strong Efficient Markets” is straw man
No info – Supply and Demand
Assume beliefs not respond to prices
Price is weighted average of beliefs
More influence: risk takers, rich
Info, Static – Rational Expectations
Price clears, but beliefs depend on price
No trade if not expect “noise traders”
Price not reveal all info
More influence: info holders

Theory II – Market Microstructure
Info, Dynamic – Game Theory
Example – Kyle ’85
X – Informed trader(s) – risk averse
Y – Noise trader – fool or liquidity pref
Market makers – no info, deep pockets
If many compete, Price = E[value|x+y]
Info markets – use risk-neutral limit
If Y larger, X larger to compensate more info gathered, so more accuracy!

Theory III – Behavioral Finance
Humans are overconfident
Far more speculative trade than need
Mere fact of disagreement shows
Overconfidence varies with person, experience, consequence severity
Implications
Price in part an ave of beliefs?
Adds noise to price aggregates?
Prices more honest than talk, polls, …

Ask the Right Questions
Cost independent of topic, but value not!
Seek high value to more accurate estimates!
Relevant standard: beat existing institutions
Where suspect more accuracy is possible
Suspect info is withheld, or not sure who has it
Prefer fun, easy to explain and judge
Prefer can let many know best estimates
Not fear reveal secrets, use fear to motivate
Avoid inducing foul play

Eight Design Issues
How avoid self-defeating prophecies?
How handle billions of possible combos?
What if terrorists lose $ to mislead us?
What if terrorists gain $ by give us info?
How not alarm public, inform terrorists?
Price can mislead if deciders know more.
Will markets induce people to lie?
Will markets help employees embezzle?

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Thoughts About &#8220-Decision Markets&#8221-:

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#1. Robin Hanson first wanted to apply his decision market concept to refine the democratic process &#8212-&#8221-vote on values but bet on beliefs&#8220-. He calls that &#8220-futarchy&#8221- (PDF) &#8212-as far as I can see, only some libertarian wackos like Chris Hibbert or Peter McCluskey bought the idea. (I&#8217-m not even sure his paper was accepted somewhere for publication.)

#2. Now, Robin Hanson tries to plug his decision market concept as a management decision tool &#8212-here&#8217-s from his Confab presentation:

Decision Market Applications

E[ Revenue | Switch ad agency? ]
E[ Revenue | Raise price 10%? ]
E[ Project done date | Drop feature? ]
E[ Project done date | Add personnel? ]
E[ Stock price | Fire CEO? ]
E[ Stock price | Acquire firm X? ]

The guy doesn&#8217-t have the slightest chance that his envisioned applications see the ray of light, one day (that is, before his head gets chopped off and frozen, shortly after his death). Basically, he wants the senior executives to be replaced with a market-generated automatism. Even if he can prove that it would lead to lead to better management decisions (and I trust him on that), he&#8217-ll encounter entrenched resistance from the same people his decision tool was created to compete with. I&#8217-d short-sell Robin Hanson on that one &#8212-with all my might, and I&#8217-d bet George Soros would see an opportunity here.

#3. The only chance the guy has would be to dig the field of management science for areas where a series of micro decisions are taken by mid-level executives or technologist or scientists or other employees &#8212-but NEVER by senior executives. In that perspective, all the examples of applications he gave above are worthless &#8212-direction the trash can of your computer (and select &#8220-empty the trash can&#8221-, to make sure they disappear for good.)

#4. Robin Hanson (who is a bright inventor) is totally incapable of seeing the light of what could be a successful innovation. The only chance the guy has would be for him to network with Silicon Valley&#8217-s geeks-turned-IT-executives, and, after a series of of pitches, maybe he would get feedback from someone who can find a mutant idea &#8212-an idea that is original, almost bizarre- an idea nobody ever thought of before. Robin Hanson, on his own, is totally incapable of thinking creatively in terms of innovation &#8212-he likes big ideas but he doesn&#8217-t get people and marketing (including internet usability). Which is why I&#8217-m suggesting to him to go West and to find his complement(s) there. That&#8217-s his only chance.

Prediction Markets, Decision Markets, and More – (PPT) – by Robin Hanson – 2006-12-13

– All speculation is “gambling”!

– In direct compare, beats alternatives – (Vs. Public Opinion – Vs. Public Experts – Vs. Private Experts)

– Advantages – (Numerically precise – Consistent across many issues – Frequently updated – Hard to manipulate – Need not say who how expert when – At least as accurate as alternatives)

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What&#8217-s above is about &#8220-prediction markets&#8221-. Now, below, here are possible instances of &#8220-decision markets&#8221- (a more complex form of prediction markets, structured to be a decision tool, not jut a forecasting tool):

Decision Market Applications

E[ Revenue | Switch ad agency? ]
E[ Revenue | Raise price 10%? ]
E[ Project done date | Drop feature? ]
E[ Project done date | Add personnel? ]
E[ Stock price | Fire CEO? ]
E[ Stock price | Acquire firm X? ]