Rah Price Manipulators

Matt Yglasias complains Climate Change Futures Markets would be manipulated:

This idea has some merit, but let’s not get carried away with ourselves. The underlying intuition here is that talk about climate change is cheap, but if we made people put their money where their mouth is we’d force them to speak honestly. The problem is that when coal and oil interests or the Koch family pays people money to mislead people about climate science or clean energy policies they are putting their money where their mouth is. Big money is at stake in this issue, and it could be easily worthwhile for polluters to lose money on a prediction market if that helped undercut support for clean energy legislation.  The problem is that just about any metric you might like becomes contaminated once people know there are large political economy stakes.

No!  Some metrics are more corruptible than others, and prediction market prices are especially incorruptible.  In fact, big money manipulators with legislative agendas would be good for climate change futures markets!  If most anyone can play, we expect a real money prediction market to get more accurate as more big money powers are known to want to manipulate them.

We have explained the mechanism in a 2009 Economica theory article, and confirmed its predictions in two lab experiment articles, one published in JEBO in 2006. Here is a summary:

If policymakers look to decision market prices as a guide to policy, others may be tempted to manipulate those prices in order to manipulate policy. Fortunately, the addition of manipulators should increase price accuracy. Manipulators are in essence noise traders, because their trades are not correlated with asset value information, and markets with more noise traders generally have more accurate prices, because more informed traders are attracted to profit from the noise traders. This predicted inability of manipulators to hurt price accuracy has been confirmed by lab experiments and in the field.

You might think this impossible if you confused ex ante and ex post manipulation effects.  Let me explain. Ex post, holding constant everyone else’s actions, the more a manipulator buys of something the higher its price, and the more he sells the lower its price.  So assuming others suspect you might have relevant info, and that they don’t know just how eager you are to manipulate, yes your actual trade can “manipulate” the price.

Nevertheless, ex ante, averaging over all the possible desires you might have to manipulate the price, and all the possible info anyone could have, the fact that someone might want to manipulate the price makes that price more accurate.  Since other traders expect to win their bets against manipulators, the heightened possibility of that such manipulators being present induces other traders to trade more and to collect more relevant info.  The net effect is more accurate prices.

Now this isn’t an absolute guarantee; the theory makes some assumptions and our lab and field data do not cover every possible contingency.  Even so, they surely create a reasonable presumption that big money manipulators are not the overwhelming disaster that Yglasias assumes.  Maybe we might, you know, actually try something before we conclude it doesn’t work.

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  • Marshall

    As I asked over at Yglesias’ place, why do we need a market for predictions about global warming? Won’t the market for carbon dioxide emissions permits allow individuals to profit if their beliefs about the cost of emissions are more accurate than the market’s?

    • http://hanson.gmu.edu Robin Hanson

      With cap n trade, we won’t know if the cap is the right level. We could also estimate the effects of geoengineering, to see how much we need to cut carbon.

      • Marshall

        It’s true that we won’t “know” if the cap is the right level, but what exactly is the reason we would expect it to be wrong? Ex ante, there was no reason to think the government would set the right level for sulfur dioxide emissions permits, yet they hired some scientists who determined a sustainable level for SO2 emissions, issued the “right” amount of permits, and pretty much everyone agrees the policy worked. It’s possible that the timing of costs associated with a gradual decline in the number of permits issued was not the global optimum, but putting all the weight on the possibility that the cap for carbon won’t be set right is a weak argument against the idea of cap and trade.

        Furthermore, I often encounter arguments of the form: we don’t need a carbon emissions regulatory scheme because geoengineering (or, more likely in my view, improvements in the efficiency of carbon-based energy) will save us and existing models of the cost of global warming don’t take them into account. But technology improvements are not in opposition to cap and trade: the whole point of pricing carbon is to create an incentive to economize. At present, the atmosphere is an unpriced resource, so why would there be innovation in order to reduce the exploitation of it?

      • http://williambswift.blogspot.com/ billswift

        >whole point of pricing carbon is to create an incentive to economize

        Bull. The cost of the fuel is incentive to economize on its use. There is no good evidence that atmospheric carbon dioxide is a negative externality, and thus NO REASON to “economize” on its production.

      • http://williambswift.blogspot.com/ billswift

        Sorry – to finish my comment. “Cap and trade” is the modern equivalent of buying indulgences in the Church of Environmentalism.

  • rob

    I agree, and made the exact same point in the comments of Yglesius. (with diff moniker)

    But: because markets have a tendency to be accurate, traders have a tendency to trust market prices as accurate. The better the trader, the more likely they are to be suspicious of a MAJOR market inefficiency. I think markets could be manipulated longer than they ought to be according the EMH because of this effect. E.g., if you are handicapping horses, and a horse’s odds seem to be way out of line — you are going to rethink your handicapping system twice before placing a huge bet.

    But I agree with you in the longer run. Manipulation will create action which attracts more action until prices become the best collective honest guess.

  • George

    Agree with you Robin. I think what you claim is pretty obvious IF the Climate Futures Markets’ contracts are technically fair and correct. Perhaps I give people the benefit of the doubt too often, but maybe Matt was concerned that the underlying contracts may be worded in a non-ideal manner and this non-ideal wording would be caused by Big Money lobbyists who hope to manipulate the market. I know Matt didn’t say that exactly, but it seems like a reasonable fear to instinctively have of the political process.

  • http://entitledtoanopinion.wordpress.com TGGP

    I’m not a contrarian on climate science, but I think it’s funny how Yglesias & co always have the image of the enemy being flush with cash, with the other side defenseless. Particularly funny comparing the CRU emails about all those grants with Steve McIntyre and his tip jar. Aren’t there moneyed interests who could benefit by tipping the scales in the other direction? “Countervailing power“, I believe is what liberal wags call it (at least when they approve).

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  • http://gavinthink.blogspot.com/ Gavin Andresen

    Can prediction markets work for bets that don’t pay off for a decade or three?

    I don’t think you’d find many climate scientists willing to bet on global temperatures over the next five or ten years; climate is too chaotic on that short a timescale.

    I know nothing about futures markets; are there actively traded futures contracts that don’t come due for 20 or 30 years?

    • http://www.bayesianinvestor.com Peter McCluskey

      There are actively traded eurodollar futures that settle nearly 10 years in the future. There has been limited trading on crude oil futures going out nearly that far. And 30 year treasury bonds bear some resemblence to long-term futures contracts. None of these show signs of being more susceptible to manipulation than short-term contracts.

      It’s important to have margin rules similar to those on the CME. An exchange run like Intrade has problems with long-term contracts being too close to 50.

    • floccina

      You only need a 51% advantage to take a bet. If you want a 30 year bet and can only get a 10 year bet you plan to bet a certain amount each year.

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  • Pablo Stafforini

    While we wait for the arrival of prediction markets to solve these and other problems, we can at least rely on how people react to the idea of such markets to identify those whose opinions should be trusted. There are very few other beliefs that tell you more about a person’s concern for the truth than his or her beliefs about prediction markets.

  • MPS

    Very interesting. I would have naively agreed with Yglesias — indeed maybe I posted something to that effect long ago in the comments to your blog.

  • Sean C.

    It’s important to note that unlike commodities, that have a finite supply of contracts, you can’t corner a prediction market.

    Theoretically, anyway. One can imagine corner cases where the manipulator has enough money to move the price despite the best efforts of the well informed, either because there aren’t many of those people, or the manipulator is extremely rich.

  • http://t-a-w.blogspot.com/ Tomasz Wegrzanowski

    You’re basically restating EMH. How about the prediction market that housing market was not in a bubble, also known as the market? It failed rather spectacularly.

    • http://hanson.gmu.edu Robin Hanson

      Imperfect estimates have errors, deviation from estimate and truth. No perfect estimates are available, so the question is: what other source offers more accurate estimates?

      • anon

        Imperfect estimates have errors, deviation from estimate and truth. No perfect estimates are available, so the question is: what other source offers more accurate estimates?

        That’s not at issue. The issue is whether large players can manipulate the market to their advantage. I expect the answer will be yes.

      • http://entitledtoanopinion.wordpress.com TGGP

        How much capital do the large players have relative to the rest of the market? If other participants think large players are distorting the market rather than betting accurately, they will be willing to put up more of their capital (they think they are selling a dollar for more than a dollar). If there are no significant barriers to entry, the potential market size is huge.

  • Julian Morrison

    If there’s manipulation, won’t people just pile in and arbitrage it?

    • quanticle

      Not necessarily. If the number of noise traders (compared to the number of rational traders) is about even, then yes, the rational traders will be able to arbitrage away manipulation and inefficiency. But, if there are many more noise traders than rational traders, the rational traders may not have the capital to arbitrage the bubble away.

      We saw this with the housing bubble and the dot-com bubble before it. There were lots of people who lost money (especially in the dot-com bubble) by betting that the bubble would burst by year x, when in fact the bubble actually burst in year x + 3. Its summed up by the old stock traders’ mantra, “The market can stay irrational longer than you can stay solvent.”

      • http://hanson.gmu.edu Robin Hanson

        Yes collective noise on a risky dimension can last when there is risk aversion. But that has little to do with manipulation.

      • anon

        Yes collective noise on a risky dimension can last when there is risk aversion. But that has little to do with manipulation.

        Recall that the manipulation here is the form of spending resources to move the market in a direction which supports a specific viewpoint, not manipulation for the purpose of making money in the market. In this case one way for manipulators to operate is to actively create noise upon which the noise traders trade. Secondly, once a market is in a non-equilibrium position that the manipulators like, they can use their resources to directly intervene in the market to move it further, or keep it out of balance and thus preventing arbitrage.

  • josh

    It all depends if we are pretending we are in a theoretical world where prediction markets are perfectly implemented and followed, or if we are in a theoretical world where the actual decision-makers of US Government decide to implement decision markets. If the latter, we would have to ask why and how this came to pass. Are decision-makers really going to decide to give up their personal influence, ie power and the status that accompanies it? Or, are they going to give up the responsibility that accompanies decision-making while retaining the power (see the relationship between science and government). If we ever see our government move toward futarchy (barring a major discontinuity) it will because people in power figured out how to do the latter.

    The corruption would, of course, come in the implementation, not necessarily in your theories, Robin.

    I realize this is all just moldbuggery, but it seems correct, and I can’t see anyway around it.

    • http://hanson.gmu.edu Robin Hanson

      So we dare not allow anything to change, for fear it is just what they would want?

      • josh

        Dare on. I just think its futile.

  • http://cob.jmu.edu/rosserjb Barkley Rosser

    Robin,

    I think prediction markets in climate will be an interesting experiment in how far they can work. I have my doubts that they can do better than some particularly smart and knowledgeable experts (whose lack of money or communications witih those with the money make them not impact the market). However, given the current strife over the science, it is hard to know who those experts are. But, I think prediction markets may do better at predicting social phenomena than events that have some strong and hard to predict natural component.

  • Ross

    Broadly speaking, government policy rearranges titles to goods from natural owners (makers and discoverers and traders) to what we might call social owners (“the people”). If a dollar can be spent to ensure a policy worth more than one dollar (plus transaction costs), then there is incentive for one to spend to purchase that political pull. As such, highly centralized authorities provide ample leverage to obtain a good return on investment through purchases of pull.

    The policy market scenario is no different. While we would not argue that a market cannot make accurate forecasts, once these forecasts themselves are given sway over actual policy, they can then provide additional extra-market returns through the policies they produce, and these returns can be more than sufficient to finance the market manipulation they require. In this regard, policy markets are strictly worse than existing futures markets; rearrangement of titles from natural owners actually prevents players from “putting their money where their mouths are”.

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  • Bill

    Robin’s analysis fails because the payoff is not just on the exchange, but outside of it.

    • http://hanson.gmu.edu Robin Hanson

      The model *includes* such outside payoffs.

      • Bill

        OK, so let’s carry the argument forward a bit.

        Let’s say it is a prediction market on global warming. And, let’s say the American Petroleum Institute (API) estimates that its members will have to retrofit refineries, and will lose sales from oil to renewables, at a total cost of $200 billion. API has an agreement among its members to pay for its bidding. API bids in the market that global warming is not caused by carbon emissions {Note: When API assesses Exxon-Mobil, it’s shareholders (btw I am a shareholder) AND its customers (including ME, who is going to bid on the other side) will pay for this}. Now, as a concerned citizen, one of millions of citizens, bids in the prediction market. But, although others bid with me, there is a free rider problem…some people do not bid or contribute, figuring, well, hell, if Bill is willing to bid, I won’t have to. Bidding proceeds until the $200 billion budget is exceeded, or bidding ends before the budget is exceeded. If few of us bid because of free rider, API/Exxon-Mobil wins (and I as a shareholder and customer!) pay for their victory.

        This all gets rather Coasian: people are forced to pay for API and its members not to pollute. Now, you might say, that’s great, but think of this example: Bill meets Robin in an alley, and Bill has a gun and says: bid away my right to use my gun (in other words, your money or your life). You pay me not to exercise the use of my weapon. Now, society says, no, you do not have a property right to use your weapon for extortion, go to jail.

        So here. You don’t have the right to bid or force me to pay for your “right” to pollute.

      • Bill

        Bottom line: in prediction markets don’t you want people to bid based on their true beliefs, and not on avoided costs (particularly if they know that the belief they bid is not true.)

      • Peter Twieg

        But, although others bid with me, there is a free rider problem…some people do not bid or contribute, figuring, well, hell, if Bill is willing to bid, I won’t have to.

        What? You stand to receive more money because Bill doesn’t bid. The benefits of your bidding are almost wholly internalized.

      • Bill

        Reply to Peter,

        Well, if there is free rider, and if I am worse off with others joining me, then it does alter incentives on one side of the prediction market, doesn’t it. And, don’t forget, as a consumer and a shareholder of Exxon, I pay for that battle on that side too. Sounds like if you believe global warming is caused by CO2 emissions, you pay a higher cost to bid your beliefs than if you do not. Do not like to play weighing games with someone who puts their thumb on the scale. Do you?

      • Bill

        The reason I assumed it didn’t was that one of your papers mentioned that retribution had to be avoided through anonymity in government prediction markets, and I regarded retribution as a negative side payment outside of the market.

      • Bill

        Reply to Peter Twieg,

        Oh, great, what you’re saying is that I have no incentive to get others to join me to oppose global warming by bidding with me in the prediction market. I don’t have to share the pot with them. Sad.

        No wonder economics is called the dismal science.

      • Peter Twieg

        No one’s saying you can’t do that if you want.

        Are you trying to imply that it’s a bad thing that people have individual incentives to fight the API? That there should be a free rider problem for people to gloriously overcome?

  • anon

    One important issue that isn’t discussed here is the time value of money. Due to the long term nature of climate change, opportunity cost will allow significant deviations in the market predictions and the smart money estimate. For example, imagine that you see that the market for a prediction is off by 20%, but the contract won’t be resolved five years. If you can find an investment that will give you a nominal return of 4%, you’ll do better investing your money in that vehicle than investing it into the prediction market.

    • http://hanson.gmu.edu Robin Hanson

      The wise bettor bets assets that appreciate.

      • anon

        The wise bettor bets assets that appreciate.

        Yes, prescience does help.

  • http://intellectual-detox.com Devin Finbarr

    From Robin Hanson’s paper:

    Of course the fact that we have a particular model illustrating these results hardly implies that these results always hold in every context. Our model assumes risk-neutrality, normally distributed values and signal errors, interior choices of information quantity, only quantal-response-type irrationality, no meta-signals about the signals of other agents, no transaction costs of trading, no budget constraints, and a single rational manipulator with quadratic manipulation preferences and a commonly known strength of desire to manipulate. However convenient these assumptions may have been for solving the model, one can reasonably question the empirical relevance of models based on them.

    No budget constraints? Commonly known strength of desire to manipulate?

    the theory makes some assumptions and our lab and field data do not cover every possible contingency

    No, it doesn’t cover the contingencies that are actually likely to exist in the real world. It boggles my mind that you keep citing this paper, when this paper very clearly makes so many dubious assumptions as to be useless for actually showing that decision markets would work in the real world.

    Furthermore, your paper glosses over two points which are vitally important: How does the question get defined? How is the outcome measured?

    If the measurement of the outcome has a lot of noise, then the impact of the manipulators becomes even more pronounced.

    If you actually care about convincing people, you should work through a real world example of how decision markets might work. Use global warming as an example. What is the question/policy posed to the market? How would the result be measured? We can then work through the logic of how actual, real world, players would respond to the market.

    • http://hanson.gmu.edu Robin Hanson

      You are clearly not familiar with the practice of academic modeling. Models are not expected to be exactly realistic to be persuasive; an exactly realistic model would be completely unwieldy. Issues of how to define and measure global warming are pretty independent of the issue of manipulation by traders; every post can’t deal with all issues.

      • http://intellectual-detox.com Devin Finbarr

        Robin-

        My beef is that in a response to a critique of decision markets in the context of a specific case ( global warming), you respond with a paper that makes assumptions that are not even close to the reality of the situation.

        Also, I am quite familiar with academic modeling. I just have very little respect for the way it is done.

        I am not against models in general. Nor am I against math, or making simplified assumptions, or for using approximations due to to time constraints. I work in software, and I often write documents to my co-workers about how I think a system should be engineered. I will use simplifications and approximations. As you say, an exact spec would be completely unwieldy. But these documents are nothing like an academic paper. Your goal is essentially an engineering goal – you are trying to examine whether a certain design will have the desired outcome. Thus I hold you to an engineering standard.

        Here is how I would alter your paper to make it a convincing engineering design document:

        a) First, start with the assumptions and explain and justify every non-obvious assumption you make. For instance, your assumption of “a commonly known strength of desire to manipulate” needs to be justified if your paper is to be at all convincing. Garbage in, garbage out, if your assumptions are not correct or not justified, nothing else in your model matters.

        b) Second, solve for the average case and the worst case, not the best case. For a model, you do not need exact numbers. Simplifications are fine. But you should attempt to use ball park figures for the average case. An “unlimited budget” is not an average case. Pick a typical securities market, and use that as a ballpark guess. Proving that your model works in a best case is a useless exercise.

        c) Third, it’s much more important to have ball park figures for all the assumptions, than in depth analysis of one aspect of the system. You do the opposite. You painstakingly write out the math, using the most advanced techniques possible, for a very narrow set of assumptions. Unfortunately, because the assumptions are so narrow, the paper is not at all convincing for any real world scenario. If you are time constrained (as we all are) It’s almost always better to do back of the envelope math for a very broad set of assumptions. Then if there is one particular area where precise math is needed to make an accurate judgment, you can add more advanced math as needed (although most of the time it turns out the back of the envelope estimates are good enough, your paper would be just as convincing if you simply cut out pages 4 through 11).

        Your paper passes muster in academia. But if your communicating on a blog frequented by engineers, you’ll need to do a lot better. Come up with a simplified model that actually makes reasonable estimations of budgets, noise in determining the asset value, knowledge about bias, etc.. Also add in a reasonable proposal for how the winner of the bet gets decided. You don’t need to be “exactly realistic”. Just get it in the right ballpark. As it is, the assumptions in your paper are so unrealistic as to make any further discussion impossible.

  • Patri Friedman

    This complaint is sad but predictable. Just as Robin says, it is the exact opposite of the truth. In my personal experience w/ prediction markets, I think one of their great weaknesses is thin markets due to adverse selection. Prediction markets work the best when there are many punters to make it worthwhile for the professionals – or at least some type of subsidy. People attempting to manipulate the markets are people subsidizing the markets, thus addressing one of the major problems!

  • George

    I think many people don’t understand prediction markets. Someone should make a YouTube video explaining this.

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  • Pavitra

    If market forces overcome the effects of manipulative noise traders, why doesn’t the same principle eliminate the effects of traders with special information about the event in question?

    How does the market distinguish between a trader who’s betting against market consensus because she knows something the other traders don’t, versus a trader who’s betting against market consensus because she wants the other traders to think she knows something they don’t?

    • http://hanson.gmu.edu Robin Hanson

      Read the post again. Ex post, it doesn’t; ex ante, it does.

  • Pavitra

    I read it again and I still don’t understand. Maybe I should clarify my question.

    I understand why price manipulators fail to make the market look the way they want, and instead make it more accurate.

    What I don’t understand is why insider traders, with access to true relevant information that the other traders cannot get merely by further research, aren’t “neutralized” by the same mechanism.

    That is: Assume a shallow consideration of a given question suggests a probability of 60%, more extensive research turns up data implying a more accurate 65%, and one insider has special data implying an even more accurate 64%. Further assume that the other traders besides the insider can’t turn up the insider’s special data with even extensive research — the only way they can learn what the insider knows, if at all, is through the insider.

    As I understand the article, if a manipulator tries to mess with the market, or if the insider tries to profit from the special data, in either case the market will settle on 65%.

    What can the insider do to prove they’re not a manipulator masquerading as an insider? If nothing, then how can the insider move the market to 64% when the manipulator can’t move it to 66%?