In 2001, DARPA started funding my Policy Analysis Market: We planned to cover eight nations. For each nation in each quarter of a year, we planned to have traders predict its military activity, political instability, economic growth, US military activity, and US financial involvement. In addition traders would predict US GDP, world trade, … and a few to-be-determined miscellaneous items. This would require a hundred or so base markets. Most important, we wanted to let our traders predict combinations of these, such has how moving US troops out of Saudi Arabia would affect political stability there, how that would affect stability in neighboring nations, and how all that might change oil prices. …
But they fall short of complete rationality for reasons other than lack of incentive. Adequate incentives are what I take this discussion to be about. I think prediction marketers would be satisfied if they had sufficiently numerous traders as rational as stock market investors. It's the potential number of traders, absent huge subsidies, that's most questionable. The main problem is that, as gambling events, prediction markets fail the excitement test.
You subsidize by having transaction gains instead of transaction costs.So you reward activity, not accuracy.
On the stockmarket rational predictors are betting massive amount of money on events that can turn out one way or the other.Rational predictors on the stock market?
In the stock market it's an empirically truth that you can make money using very simple and predicable investment strategies such as [index tracking](http://en.wikipedia.org/wik.... Such strategies would not work if everybody was using them, furthermore since they are completely predictable, hence they should be trivial to beat, yet they make money, which means that people who don't use them manage to do worse on average.
In fact, the stock average prices on the stock market fluctuate widely, and nobody (except perhaps some economists) really think these prices are accurate estimates of the holding values of the stocks.
You subsidize by having transaction gains instead of transaction costs.On the stockmarket rational predictors are betting massive amount of money on events that can turn out one way or the other.
"Since prediction markets are strictly zero sum, in order to profit predictors must be able to consistently beat the market by a margin that compensates prediction effort, transaction costs and risk aversion."
In a prediction market, the commission rate - denoted r in Parimutuel betting - can be negative.
Presumably the organization wanting the odds data would pay a commission (perhaps call this the B2B commission, for clarity) to the betting agency, equalling r plus the agencies operating costs + profit per betting pool. The value of the data to the organization should obviously exceed the (B2B) commission paid to the agency.
With a negative commission rate (aka 'house-take'), even bettors of average accuracy can break-even, better than average bettors can make consistent profits, and only poor bettors will lose in the longer-term. Therefore, the negative commission makes the prediction markets attractive betting propositions in general, but still punishes poorer judges. This suggests an optimum trade-off between betting appeal and 'punishing failure'.
An interesting aspect is the effect on the status and authority of organization leaders who partly defer to the data of prediction markets as the basis for decision making. Perhaps the commission paid to the betting agency should come partly out of their salaries?
They go to winners. Risk aversion could be overcome to make the investment perfectly rational if and only if you make the subsidy great enough. I gather that the hope is something between rational investment and outright zero-sum-game gambling. Maybe someone who would otherwise bet on the horses could be induced to bet on prediction markets because his expected loss on the prediction market, due to the subsidy, is lower than on the horses.
(Note to Drewfus: Thick markets with lots of rubes are definitely advantageous in the prediction markets, as Robin points out in his entry on subsidized prediction markets. The prediction markets want horse-track betters; yes, even slot players. You need thick and noisy markets.)
If you subsidize only those whose predictions come true, then yes, you increase their expected payoff, but the issues I pointed out remain, particularly risk aversion: subsides or not, rational predictors are not going to bet lots of money on events that can turn out one way or the other.
If you also subsidize those whose predictions come false, then you reduce the incentive to make accurate predictions. DAGGRE.org is an extreme example of this, since it rewards users for merely partecipating in the 'market', regardless of the accuracy of their predictions.
Robin sensibly maintains that if you're prepared to spend enough money, you can get enough entrants.
But what's enough? Here, Robin is purely algebraic, but theoretically, you can't count on it being enough at least until the subsidy exceeds the transactions fees plus the interest on the funds traders venture.
Then there's a net flow of money to the traders and it's not zero-sum anymore. And you can expect to make some money even when the market's predictions are very good.
The questions you raise are interesting in their broader practical application. As you pointed out in our previous discussion, once you've entered the stock market, trading there is a zero-sum game. So, why does so much trading go on? It turns out this is a very good question. Kahneman argues in Thinking, Fast and Slow that the whole trading industry is built on cognitive illusion and self-serving hype. He analyzed the data to find that traders lost money for their clients. The professional traders are beautiful examples of self-deceiving hypocrisy (with the exception of a very few who can deliver).
But I don't agree with your conclusion regarding the inherent limits of prediction markets (or by implication stock markets). If prediction is perfect, there's no incentive to trade. So what? The prediction is perfect already.
Rational predictors on the stock market?
But they fall short of complete rationality for reasons other than lack of incentive. Adequate incentives are what I take this discussion to be about. I think prediction marketers would be satisfied if they had sufficiently numerous traders as rational as stock market investors. It's the potential number of traders, absent huge subsidies, that's most questionable. The main problem is that, as gambling events, prediction markets fail the excitement test.
You subsidize by having transaction gains instead of transaction costs.
Well, yes, but there are various ways to subsidize transaction gains. The method of choice is to enlarge the pot.
You subsidize by having transaction gains instead of transaction costs.So you reward activity, not accuracy.
On the stockmarket rational predictors are betting massive amount of money on events that can turn out one way or the other.Rational predictors on the stock market?
In the stock market it's an empirically truth that you can make money using very simple and predicable investment strategies such as [index tracking](http://en.wikipedia.org/wik.... Such strategies would not work if everybody was using them, furthermore since they are completely predictable, hence they should be trivial to beat, yet they make money, which means that people who don't use them manage to do worse on average.
In fact, the stock average prices on the stock market fluctuate widely, and nobody (except perhaps some economists) really think these prices are accurate estimates of the holding values of the stocks.
You subsidize by having transaction gains instead of transaction costs.On the stockmarket rational predictors are betting massive amount of money on events that can turn out one way or the other.
Robin Hanson, congratulations.
Whew, such a crazy Idea I must participate
"Since prediction markets are strictly zero sum, in order to profit predictors must be able to consistently beat the market by a margin that compensates prediction effort, transaction costs and risk aversion."
In a prediction market, the commission rate - denoted r in Parimutuel betting - can be negative.
Presumably the organization wanting the odds data would pay a commission (perhaps call this the B2B commission, for clarity) to the betting agency, equalling r plus the agencies operating costs + profit per betting pool. The value of the data to the organization should obviously exceed the (B2B) commission paid to the agency.
With a negative commission rate (aka 'house-take'), even bettors of average accuracy can break-even, better than average bettors can make consistent profits, and only poor bettors will lose in the longer-term. Therefore, the negative commission makes the prediction markets attractive betting propositions in general, but still punishes poorer judges. This suggests an optimum trade-off between betting appeal and 'punishing failure'.
An interesting aspect is the effect on the status and authority of organization leaders who partly defer to the data of prediction markets as the basis for decision making. Perhaps the commission paid to the betting agency should come partly out of their salaries?
But how do you hand out these subsides?
They go to winners. Risk aversion could be overcome to make the investment perfectly rational if and only if you make the subsidy great enough. I gather that the hope is something between rational investment and outright zero-sum-game gambling. Maybe someone who would otherwise bet on the horses could be induced to bet on prediction markets because his expected loss on the prediction market, due to the subsidy, is lower than on the horses.
(Note to Drewfus: Thick markets with lots of rubes are definitely advantageous in the prediction markets, as Robin points out in his entry on subsidized prediction markets. The prediction markets want horse-track betters; yes, even slot players. You need thick and noisy markets.)
But how do you hand out these subsides?
If you subsidize only those whose predictions come true, then yes, you increase their expected payoff, but the issues I pointed out remain, particularly risk aversion: subsides or not, rational predictors are not going to bet lots of money on events that can turn out one way or the other.
If you also subsidize those whose predictions come false, then you reduce the incentive to make accurate predictions. DAGGRE.org is an extreme example of this, since it rewards users for merely partecipating in the 'market', regardless of the accuracy of their predictions.
Robin sensibly maintains that if you're prepared to spend enough money, you can get enough entrants.
But what's enough? Here, Robin is purely algebraic, but theoretically, you can't count on it being enough at least until the subsidy exceeds the transactions fees plus the interest on the funds traders venture.
"Since prediction markets are strictly zero sum..."
Many markets are like this, but Robin has written that he has higher expectations for markets that are subsidized by someone interested in the info:
http://www.overcomingbias.c...
Then there's a net flow of money to the traders and it's not zero-sum anymore. And you can expect to make some money even when the market's predictions are very good.
Having a parallel real money market might also reduce the incentives to distort the play money market.
Don't think this gets you off the hook on writing a book!
Congratulations!
The questions you raise are interesting in their broader practical application. As you pointed out in our previous discussion, once you've entered the stock market, trading there is a zero-sum game. So, why does so much trading go on? It turns out this is a very good question. Kahneman argues in Thinking, Fast and Slow that the whole trading industry is built on cognitive illusion and self-serving hype. He analyzed the data to find that traders lost money for their clients. The professional traders are beautiful examples of self-deceiving hypocrisy (with the exception of a very few who can deliver).
But I don't agree with your conclusion regarding the inherent limits of prediction markets (or by implication stock markets). If prediction is perfect, there's no incentive to trade. So what? The prediction is perfect already.
I'm disappointed by the restriction to US citizens. I'd very much like to see how it works.