Scott Alexander praises Polymarket's election success but argues their Trump odds were mispriced, explaining why Trump's win doesn't significantly validate their numbers over other forecasters. Longer summary

Scott Alexander congratulates Polymarket for their success during the recent election, but argues that their Trump shares were mispriced by about ten cents. He uses Bayes' Theorem to explain why Trump's victory doesn't significantly vindicate Polymarket's numbers. Scott compares the situation to non-money forecasters like Metaculus versus real-money markets like Polymarket, explaining why he initially trusted the former more. He discusses the impact of a large bettor named Theo on Polymarket's odds and addresses several objections to his argument. Scott concludes that while prediction markets are valuable, they can sometimes fail and require critical thinking. Shorter summary

The post examines the performance of prediction markets in elections, current political forecasts, and various other prediction markets, while also discussing the challenges and potential of forecasting. Longer summary

This post discusses several topics related to prediction markets and forecasting. It starts by examining a claim that prediction markets have an 'election problem', showing that real-money markets performed poorly in recent elections. The author then analyzes current polls and prediction markets for the 2024 US presidential election, noting discrepancies between different platforms. The post also explores a forecasting experiment on AI futures, and reviews several other prediction markets on current events. Finally, it includes short links to other forecasting-related news and reflections. Shorter summary