This month’s Quarterly Journal of Economics features an article by Snowberg, Wolfers, and Zitzewitz: Analyzing high frequency financial fluctuations on November 2 and 3 in 2004, we find that markets anticipated higher equity prices, interest rates and oil prices and a stronger dollar under a Bush presidency than under Kerry. … analyses of all Presidential elections since 1880 … [suggests] electing a Republican President raises equity valuations by 2-3 percent, and that since Reagan, Republican Presidents have tended to raise bond yields.
Eric, you are right, the shock due to a debate could also be a reasonable basis, and could give advice well before the election. I also agree that the method can be applied when there is just one price jump; I was just concerned about whether that would give enough statistical power.
I like the shock futures idea. At some point I think I pitched something similar to Intrade. I think it was your idea but without the denominator, i.e. "Election Day returns conditional on GDP wins" (trades unwound otherwise) and a similar contract for the Dems.
Unfortunately they (probably correctly) thought it would be too complicated for most people to want to trade. That's the frustration with a lot of otherwise cool contracts, but hopefully that'll change as the concept matures.
A couple other thoughts:
1. I completely agree on your limitation #2. One point we make in the paper is that if you regress the S&P on Prob(Bush) during the pre-election time period (i.e. a time period in which the state of the economy is affecting both), you can get very biased results.
2. Re limitation #1: I think our method would work fine if the results were announced exactly at midnight, and the probability jumped from P to 1. In that case, our regression would just yield the standard event study result, scaled appropriately by 1/(1-P) using the prediction market price. Obviously, the incremental power of the method over a traditional event study is greater when news doesn't come all at once (or can't be timed precisely).
3. Re limitation #3: if you have a setting or time period in which you are confident about the direction of causality, then you are fine. For example, we don't talk about it in the paper, but in talks I mention that we did a Wald estimator for one of the 2004 debates of dS&P/dProb(Bush). You do get results that are much less precise, (I think we got a Bush effect of 3% +/- 6%) but you can at least reject the naive pre-election estimates.
And of course, another counter example is our pre-war paper on Iraq.
Eric, you are right, the shock due to a debate could also be a reasonable basis, and could give advice well before the election. I also agree that the method can be applied when there is just one price jump; I was just concerned about whether that would give enough statistical power.
I like the shock futures idea. At some point I think I pitched something similar to Intrade. I think it was your idea but without the denominator, i.e. "Election Day returns conditional on GDP wins" (trades unwound otherwise) and a similar contract for the Dems.
Unfortunately they (probably correctly) thought it would be too complicated for most people to want to trade. That's the frustration with a lot of otherwise cool contracts, but hopefully that'll change as the concept matures.
A couple other thoughts:
1. I completely agree on your limitation #2. One point we make in the paper is that if you regress the S&P on Prob(Bush) during the pre-election time period (i.e. a time period in which the state of the economy is affecting both), you can get very biased results.
2. Re limitation #1: I think our method would work fine if the results were announced exactly at midnight, and the probability jumped from P to 1. In that case, our regression would just yield the standard event study result, scaled appropriately by 1/(1-P) using the prediction market price. Obviously, the incremental power of the method over a traditional event study is greater when news doesn't come all at once (or can't be timed precisely).
3. Re limitation #3: if you have a setting or time period in which you are confident about the direction of causality, then you are fine. For example, we don't talk about it in the paper, but in talks I mention that we did a Wald estimator for one of the 2004 debates of dS&P/dProb(Bush). You do get results that are much less precise, (I think we got a Bush effect of 3% +/- 6%) but you can at least reject the naive pre-election estimates.
And of course, another counter example is our pre-war paper on Iraq.