In my last post I said I hoped prediction markets would become an “our answers” institution with easily-found accurate answers on as many questions as possible. Today prediction markets’ main problem is laws banning them (and customs limiting firm interest in internal markers). Alas as an academic, I can’t do much to change such laws. But I can work to improve the basic tech, for the day when prediction markets are legal. Yesterday I also said:
For DAGGRE results, try the blog. For example, http://blog.daggre.org/2012.... Other results released as questions close. Search the blog for "Brier Score". Combinatorial system should come online within a month -- join!
It is hard to see how this is worse, but it is easy to see that this can still be bad. For example, if the topic is US elections, variables are ridiculously non-independent, and just letting users add correlations until the available treewidth is exhausted can lead to some really weird models, I suspect.
Just a thought: until it's legal to use actual money, you could try some sort of fake currency (like Reddit's "karma", for example). Make it a bit of a game, even.
Then hook it up to social networks, get some word-of-mouth going...
Aren't credit default swaps a specific type of prediction market? A prediction market based on who was going to default?
Wasn't the problem with credit default swaps that once the value of a credit event to those playing with the credit default swaps becomes large compared to the value of the actual credit event, there are strong incentives to game the system, plus the fact that many of the players are running on margin?
If you are betting in a prediction market (or any market) using margin, you are not using your “own” money.
We will usually start the market prices assuming that all variables are independent, and that is how they will stay until a user makes an edit to induce a correlation. It is hard to see how this is worse than a market that implicitly requires all variables to always remain independent.
I don't think there is any question that a combinatorial prediction market model has the potential to yield better predictions for some outcomes. The question is whether there exists sufficient information completeness to achieve a reasonable (and consistent) prediction.
If no one has sufficient information on which to base an accurate prediction, there is no way any market is going to provide the missing information. We can provide incentives to search for information, but that's about it. At least a combinatorial market utilizes as much of the available information as possible. Still, it may not be enough for the most important questions that we wish to predict.
@a527a356c2e9dc6fbc6067ff0648e6f3:disqus I just re-tested the "Join!" button on http://daggre.org, and it sent the registration email. If you're not getting the email, please check spam. If that doesn't work, please email or call Marva Tokhi: daggre_at_c4i.gmu.edu (replace _at_ with @) or at 703-993-2021. We had a serious backlog but you should now get a response within 24h. If not, please escalate to "daggre_admin@c4i...."
I can't claim to understand the technical details, but I thought you had previously made very clear that the only way prediction markets can work is if real people bet with real wealth. Since you apparently aren't doing that in this combinatorial market thingy that you are discussing here, what exactly are you testing and/or accomplishing? Is the purpose of the present effort to test software, user-interfaces, computer speeds, and/or various algorithms for their basic functionality, while assuming that the value of any/all of the predictions generated is zero? And.... if so, is that for the purpose that you'll be all ready to go if/when prediction markets become legal? Or something else?
When the Good Judgement ended its first season, I didn't sign up again because I wanted to try DAGGRE (I had already joined Tetlock's group before I heard of yours). But I haven't been able to sign in to that and haven't gotten a response when I emailed the contact given at the DAGGRE site.
Firepower, the Efficient Markets Hypothesis says that an economic collapse will be difficult to predict. If the information is available, speculators will start shorting/selling to bring prices down, and voila you've got a recession. Also, you seem quite confident in your beliefs even when they are wrong.
Lots of economists predicted a collapse years ahead of time, but most couldn't say exactly when and no one listened anyways. Maybe next time when they can put their money where their mouth is, we will listen.
The practical applications once widespread would be immense - we would have the best possible way to assess the likelihood of important future events. Imagine if in 2003 we heard "but Mr. President, over X million dollars says there are no WMDs in Iraq. Would you bet some of your personal fortune that there are WMDs?"
This could work, and a lot of high tree-width Bayes net applications do use Monte Carlo sampling. For prediction markets, one wouldn't have historical data to go off of, but you can still get this from the conditional estimates that you do have. One way is to calculate the conditional probability for one arbitrary node given naively chosen starting values (which is cheap), randomly set it according to those probabilities, and then move to another relevant node, again varying just it- after a while, you have a sample of the relevant distribution.
It's still worth avoiding if possible: generally, if you can figure out a way to make your system deterministic instead of stochastic, you should take it.
"Even when we can handle more realistic nets, we will still have to limit them to make computing feasible. So we’ll need ways to let users edit the net structures – to tell us where to add and delete connections. I have some ideas here, but we are a way from a satisfactory solution."
The first two things that came to mind: giving users private conditional independence networks, so that they can add or subtract arcs to their heart's content without polluting the general network, and relatedly, treating conditional independence like any other piece of knowledge in the system- one that has an attached price structure. (It would be difficult to resolve a bet on whether or not two things are conditionally independent, though, and so there might need to be a different type of price. A tax to cover the computational cost?)
For DAGGRE results, try the blog. For example, http://blog.daggre.org/2012.... Other results released as questions close. Search the blog for "Brier Score". Combinatorial system should come online within a month -- join!
It is hard to see how this is worse, but it is easy to see that this can still be bad. For example, if the topic is US elections, variables are ridiculously non-independent, and just letting users add correlations until the available treewidth is exhausted can lead to some really weird models, I suspect.
Just a thought: until it's legal to use actual money, you could try some sort of fake currency (like Reddit's "karma", for example). Make it a bit of a game, even.
Then hook it up to social networks, get some word-of-mouth going...
Aren't credit default swaps a specific type of prediction market? A prediction market based on who was going to default?
Wasn't the problem with credit default swaps that once the value of a credit event to those playing with the credit default swaps becomes large compared to the value of the actual credit event, there are strong incentives to game the system, plus the fact that many of the players are running on margin?
If you are betting in a prediction market (or any market) using margin, you are not using your “own” money.
There is a big difference between "regulated" and "banned".
When will results DAGGRE's performance be available?
UK gambling markets are heavily regulated.
We will usually start the market prices assuming that all variables are independent, and that is how they will stay until a user makes an edit to induce a correlation. It is hard to see how this is worse than a market that implicitly requires all variables to always remain independent.
I don't think there is any question that a combinatorial prediction market model has the potential to yield better predictions for some outcomes. The question is whether there exists sufficient information completeness to achieve a reasonable (and consistent) prediction.
If no one has sufficient information on which to base an accurate prediction, there is no way any market is going to provide the missing information. We can provide incentives to search for information, but that's about it. At least a combinatorial market utilizes as much of the available information as possible. Still, it may not be enough for the most important questions that we wish to predict.
@a527a356c2e9dc6fbc6067ff0648e6f3:disqus I just re-tested the "Join!" button on http://daggre.org, and it sent the registration email. If you're not getting the email, please check spam. If that doesn't work, please email or call Marva Tokhi: daggre_at_c4i.gmu.edu (replace _at_ with @) or at 703-993-2021. We had a serious backlog but you should now get a response within 24h. If not, please escalate to "daggre_admin@c4i...."
While stronger incentives give more accuracy, weaker incentives do not give zero accuracy. And yes, we do need to test software, interfaces, etc.
I can't claim to understand the technical details, but I thought you had previously made very clear that the only way prediction markets can work is if real people bet with real wealth. Since you apparently aren't doing that in this combinatorial market thingy that you are discussing here, what exactly are you testing and/or accomplishing? Is the purpose of the present effort to test software, user-interfaces, computer speeds, and/or various algorithms for their basic functionality, while assuming that the value of any/all of the predictions generated is zero? And.... if so, is that for the purpose that you'll be all ready to go if/when prediction markets become legal? Or something else?
When the Good Judgement ended its first season, I didn't sign up again because I wanted to try DAGGRE (I had already joined Tetlock's group before I heard of yours). But I haven't been able to sign in to that and haven't gotten a response when I emailed the contact given at the DAGGRE site.
Firepower, the Efficient Markets Hypothesis says that an economic collapse will be difficult to predict. If the information is available, speculators will start shorting/selling to bring prices down, and voila you've got a recession. Also, you seem quite confident in your beliefs even when they are wrong.
Lots of economists predicted a collapse years ahead of time, but most couldn't say exactly when and no one listened anyways. Maybe next time when they can put their money where their mouth is, we will listen.
The practical applications once widespread would be immense - we would have the best possible way to assess the likelihood of important future events. Imagine if in 2003 we heard "but Mr. President, over X million dollars says there are no WMDs in Iraq. Would you bet some of your personal fortune that there are WMDs?"
This could work, and a lot of high tree-width Bayes net applications do use Monte Carlo sampling. For prediction markets, one wouldn't have historical data to go off of, but you can still get this from the conditional estimates that you do have. One way is to calculate the conditional probability for one arbitrary node given naively chosen starting values (which is cheap), randomly set it according to those probabilities, and then move to another relevant node, again varying just it- after a while, you have a sample of the relevant distribution.
It's still worth avoiding if possible: generally, if you can figure out a way to make your system deterministic instead of stochastic, you should take it.
"Even when we can handle more realistic nets, we will still have to limit them to make computing feasible. So we’ll need ways to let users edit the net structures – to tell us where to add and delete connections. I have some ideas here, but we are a way from a satisfactory solution."
The first two things that came to mind: giving users private conditional independence networks, so that they can add or subtract arcs to their heart's content without polluting the general network, and relatedly, treating conditional independence like any other piece of knowledge in the system- one that has an attached price structure. (It would be difficult to resolve a bet on whether or not two things are conditionally independent, though, and so there might need to be a different type of price. A tax to cover the computational cost?)