Uploaded November 2024 | Updated September 2026, 1 week ago
Leading into the US presidential election in 2024, you had your usual gaggle of polls, poll aggregators and polling experts, all facing existential challenges in terms of sampling bias and credibility. Much as we like to complain, though, we all like predictors of who is up (preferably the candidate we like) and who is down (preferably the other candidate), and political markets like Polymarket and Kalshi stepped into the fray. In addition to providing dynamic and updated likelihoods of winning, they became part of the political discourse as both sides of the divide drew attention to market movements in their favor. In this session, I look at the political markets in the larger context of a shift in how we get the information we use to make choices on what to watch, where to eat and even what is going on from professional sources (movie and restaurant reviews, newspapers & TV) to crowds (Rotten Tomatoes, Yelp and social media). Drawing on research that we have on financial markets (which is essentially a long-lived crowd sourced estimate of value), I examine the conditions where the crowd or market judgment is wise. I am a realist, though, and there is the very real possibility that crowds can go mad in their judgments, driven by herd behavior and emotion, and I look at the conditions that give rise to that madness, as well. I end the session by looking at the trade off between the good (wisdom of crowds) and the bad (madness of crowds), and while I conclude that the net is positive, I suggest caution in how we use market (and crowd) judgments.
Slides: https://pages.stern.nyu.edu/~adamodar/pdfiles/blog/PolMkts.pdf
Blog Post: aswathdamodaran.blogspot.com/2024/11/the-wisdom-and-madness-of-crowds.html
Political Markets:
Polymarket: polymarket.com
Kalshi: kalshi.com/events/elections
Leading into the US presidential election in 2024, you had your usual gaggle of polls, poll aggregators and polling experts, all facing existential challenges in terms of sampling bias and credibility. Much as we like to complain, though, we all like predictors of who is up (preferably the candidate we like) and who is down (preferably the other candidate), and political markets like Polymarket and Kalshi stepped into the fray. In addition to providing dynamic and updated likelihoods of winning, they became part of the political discourse as both sides of the divide drew attention to market movements in their favor. In this session, I look at the political markets in the larger context of a shift in how we get the information we use to make choices on what to watch, where to eat and even what is going on from professional sources (movie and restaurant reviews, newspapers & TV) to crowds (Rotten Tomatoes, Yelp and social media). Drawing on research that we have on financial markets (which is essentially a long-lived crowd sourced estimate of value), I examine the conditions where the crowd or market judgment is wise. I am a realist, though, and there is the very real possibility that crowds can go mad in their judgments, driven by herd behavior and emotion, and I look at the conditions that give rise to that madness, as well. I end the session by looking at the trade off between the good (wisdom of crowds) and the bad (madness of crowds), and while I conclude that the net is positive, I suggest caution in how we use market (and crowd) judgments.
Slides: https://pages.stern.nyu.edu/~adamodar/pdfiles/blog/PolMkts.pdf
Blog Post: aswathdamodaran.blogspot.com/2024/11/the-wisdom-and-madness-of-crowds.html
Political Markets:
Polymarket: polymarket.com
Kalshi: kalshi.com/events/elections
