Should Google subsidize the Lunar X Prize contract on InTrade?
John Salvatier,
Our good friend Bo Cowgill might have already re-created those prediction markets on Googles internal prediction exchange at a marginal cost of zero US dollar. No nee…

I’ll miss my posting privileges here. I really will

I suspect the intention was to make the probabilities (”Dem presidency” and “non-Dem presidency”) add up to be exactly the same as the probability of any kind of presidency.

“Democratic” is the system of Democracy. Democrat is a political party in America. Although I’m sure the DNC loves how people conflate the two.

I don’t think it’s a conflation; it’s simply a word with more than one meaning. The word Republican is the same: it also has a meaning distinct from the name of a party.

(1) Column headings:
“Dem price non-Dem price Dem norm non-Dem norm”

Why not Democrat and Republican? Those are the two major parties. What about third
parties?

(2) “non-Democratic administration”

“Democratic” is the system of Democracy. Democrat is a political party in America. Although I’m sure the DNC loves how people conflate the two.

Where? Would you mind pointing me to the first comment you made in that discussion, in which you understood what I was proposing, and correctly stated what you meant? Because that was kind of an issue back then.

we expect that on election day most of the causal direction of the correlation is from the vote to the consequences, while for most days before there are large causal forces in both directions.

Well, you certainly *hope* so, but then, the market has usually largely incorporated expectations about the winner before election, making the signal really really small, and allowing the random influences to dominate.

Let me take a gander at Peter McCluskey’s shock futures market. Is it consistent with my theory that bidders will assume that other random forces will determine the election day correlation?

“49.9-50.1″

Yep, that’s betting on a coin flip alright!

Also, we want a market estimate as useful as possible right up until the election, but just before the election the overall correlation price would be dominated by the previous correlation history.

Yes, so in the unlikely event that the correlation of “probability of democratic win” and “oil futures” is very far from the unknown noise-filtered, manipulation-filtered election day correlation, this metric will have inaccurate results.

If you really think the election day’s correlation is that much more important, then you can say:

“Silas, that’s a really good idea, but to account for election day’s more relevant information, the metric should treat election day as 30 days of price history for purposes of determining the correlation that resolves the bet.”

Then, you give stronger weight to election day, but still incorporate all the available information and dilute irrelevant influences!

(And do you really imagine I had not considered your obvious variation when I chose my design?)

I invite anyone to read the thread and decide if Robin’s responses indicate that he had considered the idea before.

P(Robin responds to misunderstandings of my idea | Robin has considered my idea before) = low
P(Robin responds to misunderstandings of my idea | Robin has not considered my idea before) = high

But in principle you are right. There’s got to be some sweet spot of volume and good guesstimation of the initial line where this is profitable even with the fairly small bid/ask.

If a somewhat larger spread would still invite interest in the market, it should be fairly easy to make it profitable as long as transaction costs to the market maker are low (much smaller than the spread).

Props to Peter for taking on the risk in order to get the market going, and more props if he ends up making a profit. Anyone interested in setting up a prediction market based on whether Peter McCluskey comes out ahead?