If he had balls, Robin Hanson would debate Paul Hewitt, instead.

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Paul Hewitt: The Essential Prerequisite for Adopting Prediction Markets

It is a long text, so I will post again about it, in the near future. (Happy Xmas, by the way.)

ADDENDUM: Saturday, January 16, 2010: Debate between Robin Hanson and Mencius Moldbug

Feedback trading in prediction markets

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Robin Hanson is schooled about prediction market trading.

Our guest author to our Master Of All Universes:

Feedback trading just means the kind of momentum trading that is pervasive in traditional assets, again, less so in prediction markets. In the biastest experiment, traders were given formal &#8220-clues&#8221- about the settlement, but for many market participants, the best &#8220-clue&#8221- (even rationally, if lazy) is recent price action. Even if feedback trading was possible within the experiment, the outcome (manipulation attempts were corrected) suggests that it wasn&#8217-t prevalent.

In this experiment, traders were given equal endowments of shares/currency&#8230- i.e. initially had equal account sizes. Yes, there were an equal number of manipulators and non-manipulators, but they could not coordinate. Even if they were implicitly coordinating, this is not the same as a single large trader influencing the market. Yes, in the theory paper trading sizes were variable, but according to the same parameter for each trader. Maybe if there were a large supply of potential traders able to frictionlessly join the manipulated market, a manipulator&#8217-s relatively deep pockets wouldn&#8217-t matter.

Robin Hanson cant ignore Paul Hewitt anymore.

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Spot the comments in the following posts:

Robin Hanson to Paul Hewitt &#8211- #1

Robin Hanson to Paul Hewitt &#8211- #2

Robin Hanson to Paul Hewitt &#8211- #3

Previously: The Robin Hanson manipulation papers make unrealistic assumptions, but it’s not like prediction markets are a bad idea…!!…

The Robin Hanson manipulation papers make unrealistic assumptions, but its not like prediction markets are a bad idea…!!…

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In terms of unrealistic assumptions in Robin Hanson&#8217-s series of papers on manipulation, the major ones have been out there since at least 2004.

Despite some limited evidence, the insistence on traders needing to know the direction of manipulation isn&#8217-t too compelling since the direction will be manifest insofar as the price is &#8220-wrong.&#8221- &#8220-Noise trader&#8221- is a politically loaded and misleading term. Misleading because it suggests that the mean effect will be zero, when in reality &#8220-noise trading&#8221- usually takes the form of feedback trading. Lack of feedback trading is a significant assumption in the Hanson manipulation papers. Fortunately, prediction markets have objective settlements at specified times, unlike traditional assets where the meaning of prices is open to interpretation, making them more prone to feedback trading and irrational booms and busts.

With prediction markets, conditions for manipulation are more favorable when the settlement is far off in time, and when there are subjective inputs to the settlement, e.g. in politics. A distant settlement simultaneously makes it less clear what the real price should be, and delays manipulator losses because there is less incentive to correct price. At the limit, a manipulator could introduce a price distortion when a contract is launched, only to reverse position for small liquidity-related loss immediately before settlement, thereby destroying the markets &#8220-integral&#8221- of error over time.

Another big assumption, also identified by Paul Hewitt, is that traders have equal account sizes. But maybe this isn&#8217-t a huge problem if settlement is forthcoming, and maybe the issue could be mitigated with additional exchange disclosures, such as the standard deviation of position sizes in a given market. While this could discourage liquidity as large traders would become paranoid about their positions, it is essentially a &#8220-soft&#8221- position limit, and traders would be forewarned of one-sided markets (which could of course be the result of someone well-informed, but I &#8211- the google-anonymous* writer &#8211- would bet that more concentration comes with more error on average&#8230- this can be tested by someone with the data, of course maintaining trader anonymity)

Even accounting for long-term settlement, feedback trading, semi-subjective settlements, and account size imbalances, it seems one would have to abide to an overly rigid tenet of &#8220-do no harm&#8221- to hold that prediction markets are, on net, a bad idea. (Do no harm is of course abhorrent to libertarians, and even doctors don&#8217-t actually follow such a rule.) Moreover, some pathologies like political self-fulfilling prophecy will only happen if prediction markets have already demonstrated their value and have become more popular. But even if one believes in their long term success, single pathologies can damage one&#8217-s reputation permanently&#8230- if one plans to die at a reasonable age.

[*Given the political climate, many firms have issued directives to employees to not engage in even the slightest appearance of impropriety, which might include blogging on manipulation.]

Alain Badiou = Being and Event = Mathematics as Ontology

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Niall O&#8217-Connor has more in common with Robin Hanson than you would have thought one hour ago: They both love philosophy (i.e., blah blah blah).

Niall O&#8217-Connor:

Chris,

On a broader point, you would be well served as a Frenchman to promote Badiou and his notion of “mathematics as ontology”. Moreover, you and your merry band of readers would all do well to put Badiou’s “Being and Event” on your holiday reading lists- for a little light vacation reading.

Wikipedia:

Introduction to Being and Event
Drawing from 8 March 2006 &#8220-Art&#8217-s Imperative&#8221- lecture

The major propositions of Badiou&#8217-s philosophy all find their basis in Being and Event, in which he continues his attempt (which he began in Theorie du sujet) to reconcile a notion of the subject with ontology, and in particular post-structuralist and constructivist ontologies.[3] A frequent criticism of post structuralist work is that it prohibits, through its fixation on semiotics and language, any notion of a subject. Badiou&#8217-s work is, by his own admission,[4] an attempt to break out of contemporary philosophy&#8217-s fixation upon language, which he sees almost as a straitjacket. This effort leads him, in Being and Event, to combine rigorous mathematical formulae with his readings of poets such as Mallarme and Holderlin and religious thinkers such as Pascal. His philosophy draws equally upon &#8216-analytical&#8217- and &#8216-continental&#8217- traditions. In Badiou&#8217-s own opinion, this combination places him awkwardly relative to his contemporaries, meaning that his work had been only slowly taken up.[5] Being and Event offers an example of this slow uptake, in fact: it was translated into English only in 2005, a full seventeen years after its French publication.

As is implied in the title of the book, two elements mark the thesis of Being and Event: the place of ontology, or &#8216-the science of being qua being&#8217- (being in itself), and the place of the event — which is seen as a rupture in ontology — through which the subject finds his or her realization and reconciliation with truth. This situation of being and the rupture which characterizes the event are thought in terms of set theory, and specifically Zermelo–Fraenkel set theory (with the axiom of choice), to which Badiou accords a fundamental role in a manner quite distinct from the majority of either mathematicians or philosophers.

Mathematics as ontology

For Badiou the problem which the Greek tradition of philosophy has faced and never satisfactorily dealt with is the problem that while beings themselves are plural, and thought in terms of multiplicity, being itself is thought to be singular- that is, it is thought in terms of the one. He proposes as the solution to this impasse the following declaration: that the one is not. This is why Badiou accords set theory (the axioms of which he refers to as the Ideas of the multiple) such stature, and refers to mathematics as the very place of ontology: Only set theory allows one to conceive a &#8216-pure doctrine of the multiple&#8217-. Set theory does not operate in terms of definite individual elements in groupings but only functions insofar as what belongs to a set is of the same relation as that set (that is, another set too). What separates sets out therefore is not an existential positive proposition, but other multiples whose properties validate its presentation- which is to say their structural relation. The structure of being thus secures the regime of the count-as-one. So if one is to think of a set — for instance, the set of people, or humanity — as counting as one the elements which belong to that set, it can then secure the multiple (the multiplicities of humans) as one consistent concept (humanity), but only in terms of what does not belong to that set. What is, in following, crucial for Badiou is that the structural form of the count-as-one, which makes multiplicities thinkable, implies that the proper name of being does not belong to an element as such (an original &#8216-one&#8217-), but rather the void set (written O), the set to which nothing (not even the void set itself) belongs. It may help to understand the concept &#8216-count-as-one&#8217- if it is associated with the concept of &#8216-terming&#8217-: a multiple is not one, but it is referred to with &#8216-multiple&#8217-: one word. To count a set as one is to mention that set. How the being of terms such as &#8216-multiple&#8217- does not contradict the non-being of the one can be understood by considering the multiple nature of terminology: for there to be a term without there also being a system of terminology, within which the difference between terms gives context and meaning to any one term, does not coincide with what is understood by &#8216-terminology&#8217-, which is precisely difference (thus multiplicity) conditioning meaning. Since the idea of conceiving of a term without meaning does not compute, the count-as-one is a structural effect or a situational operation and not an event of truth. Multiples which are &#8216-composed&#8217- or &#8216-consistent&#8217- are count-effects- inconsistent multiplicity is the presentation of presentation.

Badiou&#8217-s use of set theory in this manner is not just illustrative or heuristic. Badiou uses the axioms of Zermelo–Fraenkel set theory to identify the relationship of being to history, Nature, the State, and God. Most significantly this use means that (as with set theory) there is a strict prohibition on self-belonging- a set cannot contain or belong to itself. Russell&#8217-s paradox famously ruled that possibility out of formal logic. (This paradox can be thought through in terms of a &#8216-list of lists that do not contain themselves&#8217-: if such a list does not write itself on the list the property is incomplete, as there will be one missing- if it does, it is no longer a list that does not contain itself.) So too does the axiom of foundation — or to give an alternative name the axiom of regularity — enact such a prohibition (cf. p. 190 in Being and Event). (This axiom states that all sets contain an element for which only the void [empty] set names what is common to both the set and its element.) Badiou&#8217-s philosophy draws two major implications from this prohibition. Firstly, it secures the inexistence of the &#8216-one&#8217-: there cannot be a grand overarching set, and thus it is fallacious to conceive of a grand cosmos, a whole Nature, or a Being of God. Badiou is therefore — against Cantor, from whom he draws heavily — staunchly atheist. However, secondly, this prohibition prompts him to introduce the event. Because, according to Badiou, the axiom of foundation &#8216-founds&#8217- all sets in the void, it ties all being to the historico-social situation of the multiplicities of de-centred sets — thereby effacing the positivity of subjective action, or an entirely &#8216-new&#8217- occurrence. And whilst this is acceptable ontologically, it is unacceptable, Badiou holds, philosophically. Set theory mathematics has consequently &#8216-pragmatically abandoned&#8217- an area which philosophy cannot. And so, Badiou argues, there is therefore only one possibility remaining: that ontology can say nothing about the event.

Videos:

Robin Hanson: My best idea was prediction markets.

Robin Hanson&#8216-s auto-biography (i.e., how Our Master Of All Universes views HimSelf):

robin-hanson-drink

Robin Hanson:

Do you find it hard to summarize yourself in a few words? Me too.

But I love the above quote. I have a passion, a sacred quest, to understand everything, and to save the world. I am addicted to a€?viewquakesa€?, insights which dramatically change my world view. I loved science fiction as a child, and have studied physics, philosophy, artificial intelligence, economics, and political science a€” all fields full of such insights. Unfortunately, this also tempted me to leave subjects after mastering their major insights.

I also have a rather critical style. I beat hard on new ideas, seek out critics, and then pledge my allegiance only to those still left standing. In conversation, I prefer to identify a claim at issue, and then focus on analyzing it, rather than the usual quick tours past hundreds of issues. I have always asked questions, even when I was very young.

I have little patience with those whose thinking is sloppy, small, or devoid of abstraction. And Ia€™m not a joiner– I rebel against groups with a€?our beliefsa€?, especially when members must keep criticisms private, so as not to give ammunition to a€?them.a€?A  I love to argue one on one, and common beliefs are not important for friendship a€” instead I value honesty and passion.

In a€?77 I began college (UCI) in engineering, but switched to physics to really understand the equations.A  Two years in, when physics repeated the same concepts with more math,A  I studied physics on my own, skipping the homework but acing the exams.A  To dig deeper, I did philosophy of science grad school (U Chicago), switched back to physics, and was then seduced to Silicon Valley.

By day I did artificial intelligence (Lockheed, NASA), and by night I studied on my own (Stanford) and hung with Xanadua€™s libertarian web pioneers and futurists.A  I had a hobby of institution designmy best idea was idea futures, now know as prediction markets. Feeling stuck without contacts and credentials, I went for a Ph.D. in social science (Caltech).

The physicist in me respected only econ experiments at first, but I was soon persuaded econ theory was full of insight, and did a theory thesis, and a bit of futurism on the side.A  I landed a health policy postdoc, where I was shocked to learn of medicinea€™s impotency.A  I finally landed a tenure-track job (GMU), and also found the wide-ranging intellectual conversations Ia€™d lacked since Xanadu.

My Policy Analysis Market project hit the press shit fan in a€?03, burying me in media attention for a while, and helping to kickstart the prediction market industry, which continues to grow and for which I continue to consult.A  The press flap also tipped me over the tenure edge in a€?05- my colleagues liked my being denounced by Senators. :)Tenure allowed me to maintain my diverse research agenda, and to start blogging at Overcoming Bias in November a€?06, about the same time I became a research associate at Oxforda€™s Future of Humanity Institute.

My more professional bio is here.

Robin Hanson is an associate professor of economics at George Mason University, and a research associate at the Future of Humanity Institute of Oxford University. After receiving his Ph.D. in social science from the California Institute of Technology in 1997, Robin was a Robert Wood Johnson Foundation health policy scholar at the University of California at Berkeley. In 1984, Robin received a masters in physics and a masters in the philosophy of science from the University of Chicago, and afterward spent nine years researching artificial intelligence, Bayesian statistics, and hypertext publishing at Lockheed, NASA, and independently.

Robin has over 70 publications, including articles in Applied Optics, Business Week, CATO Journal, Communications of the ACM, Economics Letters, Econometrica, Economics of Governance, Extropy, Forbes, Foundations of Physics, IEEE Intelligent Systems, Information Systems Frontiers, Innovations, International Joint Conference on Artificial Intelligence, Journal of Economic Behavior and Organization, Journal of Evolution and Technology, Journal of Law Economics and Policy, Journal of Political Philosophy, Journal of Prediction Markets, Journal of Public Economics, Medical Hypotheses, Proceedings of the Royal Society, Public Choice, Social Epistemology, Social Philosophy and Policy, Theory and Decision, and Wired.

Robin has pioneered prediction markets, also known as information markets or idea futures, since 1988. He was the first to write in detail about people creating and subsidizing markets in order to gain better estimates on those topics. Robin was a principal architect of the first internal corporate markets, at Xanadu in 1990, of the first web markets, the Foresight Exchange since 1994, and of DARPA&#8217-s Policy Analysis Market, from 2001 to 2003. Robin has developed new technologies for conditional, combinatorial, and intermediated trading, and has studied insider trading, manipulation, and other foul play. Robin has written and spoken widely on the application of idea futures to business and policy, being mentioned in over one hundred press articles on the subject, and advising many ventures, including Consensus Point, GuessNow, Newsfutures, Particle Financial, Prophet Street, Trilogy Advisors, XPree, YooNew, and undisclosable defense research projects.

Robin has diverse research interests, with papers on spatial product competition, health incentive contracts, group insurance, product bans, evolutionary psychology and bioethics of health care, voter information incentives, incentives to fake expertize, Bayesian classification, agreeing to disagree, self-deception in disagreement, probability elicitation, wiretaps, image reconstruction, the history of science prizes, reversible computation, the origin of life, the survival of humanity, very long term economic growth, growth given machine intelligence, and interstellar colonization.