Jason Ruspini:

Unfortunately, election contracts and ALL event contracts appear to be prohibited by CFTC regulation 40.11, released in July 2011 as part of Dodd-Frank:

“(a) Prohibition. A registered entity shall not list for trading or accept for clearing on or through the registered entity any of the following:

(1) An agreement, contract, transaction, or swap based upon an excluded commodity, as defined in Section 1a(19)(iv) of the Act, that involves, relates to, or references terrorism, assassination, war, gaming, or an activity that is unlawful under any State or Federal law”

“… involves, relates to … an activity that is unlawful under any State or Federal law” is very broad. Not only does it include election outcomes, which several States have explicit laws against, but Massachusetts, Mississippi, Nebraska, North Dakota and South Carolina have laws against bets on “events”.

This is not the only reading of 40.11 and is certainly not the one Nadex holds. In the short term, it seems that any argument for this sort of contract has to address the broad interpretation above all.

We are academic researchers who study prediction markets. We are writing in favor of allowing NADEX, or a similar entity, to offer a broad range of political and policy event futures, including the three they are currently proposing.

There are four broad reasons for our support:

1. Existing political event futures have proven useful. Political event futures have been offered in small quantities by the onshore Iowa Electronic Markets (IEM), and by offshore exchanges such as Intrade. Prices from these markets have made possible a broad range of academic research.

2. Political event futures facilitate price discovery in other asset markets. One of the findings of this research is that firms and industries are exposed to political and policy risk. Political event futures provide investors with a market-based assessment of outcome probabilities, which reduces investors’ uncertainty when trading other assets. In addition, if allowed to operate onshore, political event futures markets might eventually grow to the point where they might provide useful hedging opportunities for firms. The currently proposed position limits are likely sufficient for most individuals to hedge their personal exposure to election outcomes.

3. The full potential of political event futures cannot be realized in academic-scale markets or offshore. Despite the utility of the IEM and Intrade, both markets are hampered by the current regulatory environment. An onshore exchange that allowed positions of the size NADEX is suggesting could ultimately reach a scale where it could attract liquidity to contracts that currently do not succeed on Intrade. There are many exciting potential applications of such markets, in research and policy making. Offering contracts on questions of great popular interest (such as Presidential elections) is crucial to attracting investors to an exchange. Once there, they face lower costs of participating in other markets, such as those currently offered by NADEX.

4. Concerns about gambling and manipulation are misplaced. Trading securities whose payoffs depend on political outcomes is no more “gaming” than trading securities whose payoffs depend on commodity or equity prices. Clearly, one can trade any security out of gambling motives, so the key question is whether the subject of these contracts is a “game,” or an economically important event. It is hard to argue that elections are not economically important events.

One might be concerned with two forms of manipulation: outcome and price manipulation. Many individuals have already large stakes in election outcomes; for example, a top executive in a public company will have will have a significant exposure via their equity holdings, as well as through any impact of the election on policies such as tax rates. Many individuals also have substantial exposure to election outcomes via their careers. Given the position limits proposed by NADEX, the market is likely to make at most a small contribution towards the number of individuals with meaningful stakes in election outcomes. One might be concerned with trading by those involved in supervising elections, and it might be reasonable for policy to prohibit trading by those individuals.

Turning to price manipulation, there have been a couple episodes that appeared to be attempt by traders to influence perceptions of an election by manipulating prediction market prices. The evidence suggests that effects on prices are relative short-lived, and effects on perceptions are often counter-productive for the manipulator (e.g., through media stories mentioning the manipulation). Onshore election markets will likely be significantly more liquid, making price manipulation even less attractive. A further protection comes from the fact that the outcomes of interest (election winners) will be linked to prediction market prices only through perceptions. Concern about price manipulation might be better devoted to cash-settled futures, where contracts settle based on other financial market prices.

To summarize, we view markets in securities contingent on economically-relevant events as an innovation that generate positive externalities (by aggregating information) as well as benefits to participants. Innovations with positive externalities should be encouraged by policy makers, not limited. If the Commission has questions about any of the statements made or research mentioned in this letter, it should feel free to contact any of the undersigned.

- How to Manufacture a Climate Consensus – About expelling the non-believers from the academic journals publishing on climate science

- The Dog Ate Global Warming – About the destruction of raw temperature data of Planet Earth

More info on climate change.

P.S.: East Anglia e-mails (CRU)

While this made sense for a young discipline, our field has matured and the conference model has fractured the discipline and skewered it toward short-term, deadline-driven research. Computer science should refocus the conference system on its primary purpose of bringing researchers together. We should use archive sites as the main method of quick paper dissemination and the journal system as the vehicle for advancing researchers’ reputations.

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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 “viewquakes”, 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 — 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 I’m not a joiner; I rebel against groups with “our beliefs”, especially when members must keep criticisms private, so as not to give ammunition to “them.”  I love to argue one on one, and common beliefs are not important for friendship — instead I value honesty and passion.

In ‘77 I began college (UCI) in engineering, but switched to physics to really understand the equations.  Two years in, when physics repeated the same concepts with more math,  I studied physics on my own, skipping the homework but acing the exams.  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 Xanadu’s libertarian web pioneers and futurists.  I had a hobby of institution design; my 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.  I landed a health policy postdoc, where I was shocked to learn of medicine’s impotency.  I finally landed a tenure-track job (GMU), and also found the wide-ranging intellectual conversations I’d lacked since Xanadu.

My Policy Analysis Market project hit the press shit fan in ‘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.  The press flap also tipped me over the tenure edge in ‘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 ‘06, about the same time I became a research associate at Oxford’s Future of Humanity Institute.

My more professional bio is here.

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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’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.

I would go with the commonsensical view that academia is primarily an institution for teaching and research. I think of the credentialing as a byproduct.

Sounds logical.

How much consulting and speaking fees (plus, free meals, tickets, trips or the like) do our economics professors receive from the prediction market industry?

Does it taint what they write and teach?

Should we ban prediction market companies from providing any academic funding?

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Yiling Chen, now at Harvard

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Publications

An Empirical Study of Dynamic Pari-mutuel Markets: Evidence from the Tech Buzz Game [PDF, 380k]

Yiling Chen, David M. Pennock, and Tejaswi Kasturi

The 10th Workshop on Web Mining and Web Usage Analysis (WebKDD), in conjunction with the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Las Vegas, NV, August 2008.
Sharing Online Advertising Revenue with Consumers [PDF, 380k]

Yiling Chen, Arpita Ghosh, R. Preston McAfee, and David M. Pennock

The 4th Workshop on Ad Auctions, in conjunction with the 9th ACM Conference on Electronic Commerce (EC), Chicago, IL, June 2008.

Complexity of Combinatorial Market Makers [PDF, 240k]

Yiling Chen, Lance Fortnow, Nicolas Lambert, David M. Pennock, and Jennifer Wortman

The 9th ACM Conference on Electronic Commerce (EC), Chicago, IL, June 2008.

Self-Financed Wagering Mechanisms for Forecasting [PDF, 268k]

Nicolas Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel Reeves, Yoav Shoham, and David M. Pennock

The 9th ACM Conference on Electronic Commerce (EC), Chicago, IL, June 2008.

Winner of an Outstanding Paper Award at EC

A preliminary version titled “Betting with Budgets” appeared in the DIMACS Workshop on the Boundary Between Economic Theory and Computer Science, October 2007.

Pricing Combinatorial Markets for Tournaments [PDF, 520k]

Yiling Chen, Sharad Goel, and David M. Pennock

The 40th ACM Symposium on Theory of Computing (STOC), Victoria (BC), Canada, May 2008.

Combinatorial Betting [PDF, 124k]

Yiling Chen, Lance Fortnow, Evdokia Nikolova, and David M. Pennock

ACM SIGecom Exchanges, special issue on combinatorial auctions, vol. 7, no. 1, 2007.

Bluffing and Strategic Reticence in Prediction Markets [PDF, 146k]

Yiling Chen, Daniel M. Reeves, David M. Pennock, Robin D. Hanson, Lance Fortnow, and Rica Gonen

Proc. of the International Workshop on Internet and Network Economics (WINE), San Diego, CA, December 2007.

A preliminary version appeared at The Second Workshop on Prediction Markets, in conjunction with ACM Conference of Electronic Commerce (EC), San Diego, CA, June 2007.

A longer version with complete proofs [PDF, 204k]

A Utility Framework for Bounded-Loss Market Makers [PDF, 183k]

Yiling Chen and David M. Pennock

Proc. of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI), pp. 49–56, Vancouver, BC Canada, July 2007.

A longer version with complete proofs in Appendix [PDF, 244k]

Betting on Permutations [PDF, 175k]

Yiling Chen, Lance Fortnow, Evdokia Nikolova, and David M. Pennock

Proc. of the 8th ACM Conference on Electronic Commerce (EC), pp. 326–335, San Diego, CA, June 2007.

Socially Embedded Prediction Markets [PDF, 281k]

Yiling Chen and David M. Pennock

Special Issue Workshop for Economica on: The Growth of Gambling and Prediction Markets: Economic and Financial Implication, Palm Desert, CA, May 2007.

Predicting Uncertain Outcomes Using Information Markets: Trader Behavior and Information Aggregation [PDF, 250k]

Yiling Chen, Chao-Hsien Chu, and Tracy Mullen

New Mathematics and Natural Computation, vol. 2, no. 3, 2006.

An In-Depth Analysis of Information Markets with Aggregate Uncertainty [PDF, 348k]

Yiling Chen, Tracy Mullen, and Chao-Hsien Chu

Electronic Commerce Research, vol. 6, no. 2, pp. 201–22, 2006.

Information Markets vs. Opinion Pools: An Empirical Comparison [PDF, 214k]

Yiling Chen, Chao-Hsien Chu, Tracy Mullen, and David M.Pennock

Proc. of the 6th ACM Conference on Electronic Commerce (EC), pp. 58–67, Vancouver, BC Canada, June 2005.

Predicting Uncertain Outcomes Using Information Markets [PDF, 54k]

Yiling Chen, Tracy Mullen, and Chao-Hsien Chu

Proc. of the 8th Joint Conference on Information Sciences (JCIS), Salt Lake City, UT, July 2005.

Theoretical Investigation of Prediction Markets with Aggregate Uncertainty [PDF, 89k]

Yiling Chen, Tracy Mullen, and Chao-Hsien Chu

Proc. of the 7th International Conference on Electronic Commerce Research (ICECR), pp. 81–90, Dallas, TX, June 2004.

A Bipartite Graph Co-Clustering Approach for Ontology Mapping [PDF, 137k]

Yiling Chen and Frederico Fonseca,

Workshop of Semantic Web Technologies for Searching and Retrieving Scientific Data, in conjunction with the 2nd International Semantic Web Conference (ISWC), Sanibel Island, FL, October, 2003.

An Introduction to Support Vector Machines: A Review [PDF, 13k]

Yiling Chen and Isaac G. Council

AI Magazine, vol. 24, no.2, pp. 105–106, 2003.

An Empirical Study on the Relationship between Price Changes and Trading Volume in China Stock Market (In Chinese)

Yiling Chen, and Fengming Song

Journal of Management Sciences in China, vol.3 no.2, pp. 62–68, 2000.

Theses

Markets as an Information Aggregation Mechanism for Decision Support [PDF, 630k]

Ph.D. Dissertation, School of Information Sciences and Technology, The Pennsylvania State University, December 2005.

An Empirical Study on the Relationship between Price Changes and Trading Volume in China Stock Market

MS Thesis, School of Economics and Management, Tsinghua University, Beijing, China, June 1999.

Tutorial

Prediction Markets: Economics, Computation, and Mechanism Design [PDF, 1795k]

A half-day tutorial at ACM Conference on Electronic Commerce (EC), San Diego, CA, June, 2007.

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PS: With Lance Fortnow and Daniel Reeves, Yiling Chen is a member of the Pennock gang.