Why did Manifold incorrectly predict the 2024 election?
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48
Ṁ3996
Jan 21
86%
It was a coinflip and Manifold was reasonable, sigh
61%
Too heavy of a reliance on polling and forecasts
45%
Too optimistic about Democrats
42%
Echo chamber effects within the platform
37%
Real money is a better indicator than play money
25%
Underestimation of voter turnout impact
16%
Influence of large traders skewing market prices
15%
Failure to account for changing voter demographics
15%
Insufficient weighting of economic indicators
15%
Insufficient consideration of undecided voters
4%
Impact of widespread disinformation

Manifold was fairly incorrect in its predictions for the 2024 US presidential election. Why was that?

Manifold was considerably worse than real-money markets such as Polymarket, and very similar to forecasts like FiveThirtyEight and Nate Silver. It seemed to notably underestimate Trump's performance, especially in swing states (Manifold had Harris winning MI at about 65% on election day). I have noticed a very large sentiment in the Manifold community that is eager to disregard the accuracy of those who did make better predictions, oftentimes dismissing them as "lucky guesses". Is that really the case? Can we assume that Manifold will do better next time around, or has real-money betting taken over as the most reliable predictor for future elections?

How this will resolve:

Until 1/20, traders can bet on the options provided and will be able to add their own options (I will prevent the adding of options when it reaches 25). Once the market is closed, I will make one comment for each option on the market. The top three comments in like margin (likes - dislikes) will resolve YES and the remaining options will resolve NO.

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I don’t doubt that there is a possibility Manifold was in fact correct in predicting that it was a toss up. However, what concrete evidence do we have to believe that it will be more reliable than real money markets in the future?

To answer the converse (why Polymarket did) - because of a random French whale that acquired more info at cost, for the potential gain

@barbarous I am not fully educated on what exactly happened here. Is such accurate information actually available at a cost?

@vibhav by "at cost" I mean he conducted his own survey using a method that is thought to be more accurate under preference falsification. I.e. instead of asking "who will you vote for?" he asked "who will your neighbour vote for?"

@barbarous very interesting. can this consistently be reliable or did it just work in this case? if the former, why are we not relying on methods like this to forecast?

@vibhav I don't really know, but he's ended up pushing the polymarket odds by a fair amount in the correct direction and won a lot of money. So it worked for him and it worked in this case.

He also had a strong hunch that polls and other models were still underestimating trump's advantage. That's not exactly a formal model that you can apply to every case, but the beauty of prediction markets is that you can incorporate information like that and have it pay off if you increased accuracy

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Why was Manifold wrong?

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