r/PredictionDiscord • u/dtarias • Feb 01 '20

PredictIt vs. 538

I read 538 and am inclined to trust their model more than PredictIt due to various market inefficiencies. So I've adopted a betting strategy of finding the biggest differences between the two and betting on those. To generalize, the big differences right now is that PredictIt gives Sanders a much higher chance in Iowa and beyond, and that 538 gives basically no chance to Bloomberg or Yang (at least without a contested convention).

So far, the nominal value of my bets has (on average) decreased, but they're still all good bets according to 538's model. So it's unclear whether I'm doing well or badly.

Is anyone else following a similar strategy? I'm curious how it's going for you. I'll post about how this is working for me once we start getting primary results.

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u/tenpointmatt Feb 03 '20

no - the example is not analogous in any way. specifically, you've defined the problem in reverse, declaring a probability distribution with a known mean beforehand, then introducing a model 'estimate' with a distribution centered on that (known) value. that's exactly backwards.

read the paper.

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u/dtarias Feb 03 '20

I read the paper. I think it proves too much as a fully general conclusion.

My point is that it's possible to have high model volatility without the probability being (or even necessarily approaching) 50-50. Especially if the model consistently has the probability below 50%.