I met Lukas Biewald at CI Foo [1 2 3 4 5 6]. Lukas is involved in a fascinating startup called Dolores Labs that helps crowdsource your problem to Amazon’s Mechanical Turk. Read his manifesto.
As an experiment, they hired Turkers to label a sample of news items about Barack Obama and Hillary Clinton as either positive or negative for each of the candidates. As it turns out, every news source was pro-Obama except ABC News, with Digg being the pro-est of the pro-Obama camp.
They then plotted changes in news sentiment alongside the price of Obama’s intrade contract:
Visually, there appears to be a correlation and news sentiment may actually be the leading indicator between the two, however it would be great to see statistical confirmation, if it’s even possible with such a small sample.
I sent Lukas some poll data and search buzz data that we’ve been collecting for the Yahoo! Election Dashboard. I’ll post an update if anything interesting results from lining up all four signals.
It is a really small sample, but these guys did find some value in parsing news:
http://www.seas.upenn.edu/~cse400/CSE401_2007/GilderLerman/paper.pdf
But in terms of using this as a trading strategy, the rub I think would be transaction costs, which they don’t address at all.
Likewise if a market shows a positive serial correlation, that doesn’t mean you can profit from it – because your transaction costs from getting in and out frequently will very likely cause you to lose in the long run even if the signal is “good”.
Thanks Jason: looks like a fascinating study.
wow, another Jason said what I’m going to say, cool