macroeconomics

Tiger Researc
2026-10-23 05:54:18

Tiger Research says prediction markets are evolving into data infrastructure

Tiger Research argues that the real value of prediction markets lies less in trading itself and more in the probability data they generate. In its latest report, the firm says major financial media outlets including Google Finance, CNBC, CNN and The Wall Street Journal have begun displaying prediction-market probabilities, while Intercontinental Exchange and Tradeweb now distribute such data to institutional clients. A Federal Reserve working paper also cited prediction-market data as a benchmark for macro expectations across rates, inflation, unemployment and GDP growth. The report breaks the case into three parts: why market prices can serve as useful data, where those data are already being used, and whether current platforms are producing information of sufficient quality. It points to election forecasting, macroeconomic releases, public health monitoring, internal corporate forecasting and geopolitical analysis as areas where prediction markets have shown practical value. Tiger Research also analyzes public API data from the on-chain platform Limitless as of October 2026, saying the platform’s markets show broad category coverage, generally strong calibration and fast reactions to new information, though liquidity remains uneven in some contracts. The report concludes that prediction markets still face regulatory skepticism in many Asian jurisdictions and elsewhere, where they are often treated as gambling. It says broader adoption will depend on better market design, stronger regulatory engagement and more transparent data access.

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Tiger Research says prediction markets are evolving into data infrastructure
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CF40
2026-07-30 00:54:15

CF40 report says top 10% of U.S. households captured 88% of AI-era equity gains

A quarterly macro policy report released by the China Finance 40 Forum, or CF40, argues that artificial intelligence is expanding the overall wealth pool while also worsening distributional imbalances. The report says U.S. household directly held equity wealth rose from about $29 trillion in 2019 to roughly $55 trillion in the first quarter of 2026, with the sharpest expansion coming after 2023 during the AI-driven rise in stock prices. From 2022 to the first quarter of 2026, directly held equity wealth increased by about $21 trillion, and the top 10% of households took around 88% of that gain, or $18.5 trillion, while the bottom 50% received about 1%, or $0.2 trillion. At the report briefing on July 27, Huang Yiping, a CF40 member and dean of the National School of Development at Peking University, said major technological breakthroughs have repeatedly reshaped income distribution in history. He said AI may affect distribution through four channels: capital bias, task substitution, skill polarization with a digital divide, and a wealth amplification effect. The report and its presenters also warned that if income shifts from labor to capital, aggregate demand may weaken. Huang proposed a three-part policy response built around defense, empowerment, and rebalancing, while Zhang Bin said stronger productivity does not necessarily translate into faster growth if demand becomes the weaker side of the economy.

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CF40 report says top 10% of U.S. households captured 88% of AI-era equity gains