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北大数字金融Workshop第三讲预告 | Dexin Zhou, Baruch Zicklin
- 来源：
- 学校官网
- 收录时间：
- 2026-06-25 18:39:16
- 时间：
- 2026-03-31 14:00:00
- 地点：
- 北京大学国家发展研究院承泽园校区245教室
- 报告人：
- Dexin Zhou
- 学校：
- 北京大学
- 关键词：
- price discovery, prediction markets, liquidity, arbitrage, order imbalance, election forecasting
- 简介：
- This study provides the first evidence on price discovery dynamics across modern prediction markets. We study a unique dataset of common contracts traded on leading prediction markets, Polymarket, Kalshi, PredictIt, and Robinhood, during the period leading up to the 2024 U.S. presidential election. We find that more liquid prediction markets substantially outperform polls in predicting subsequent election results, yet there are significant price disparities across platforms. Polymarket leads Kalshi in price discovery, particularly when liquidity and trading activity are high, implying economically meaningful arbitrage opportunities. Moreover, net order imbalance from large trades strongly predicts subsequent returns, and the market experiencing greater directional order flow from large trades tends to lead price discovery. These results underscore how platform structure, liquidity, and informed trading interact to shape trading and prices.
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报告介绍：
This study provides the first evidence on price discovery dynamics across modern prediction markets. We study a unique dataset of common contracts traded on leading prediction markets, Polymarket, Kalshi, PredictIt, and Robinhood, during the period leading up to the 2024 U.S. presidential election. We find that more liquid prediction markets substantially outperform polls in predicting subsequent election results, yet there are significant price disparities across platforms. Polymarket leads Kalshi in price discovery, particularly when liquidity and trading activity are high, implying economically meaningful arbitrage opportunities. Moreover, net order imbalance from large trades strongly predicts subsequent returns, and the market experiencing greater directional order flow from large trades tends to lead price discovery. These results underscore how platform structure, liquidity, and informed trading interact to shape trading and prices.
报告人介绍：
Dr. Dexin Zhou is an Associate Professor of Economics and Finance at Baruch College, City University of New York. His work examines the roles of media, social networks, and institutional investors in financial markets. Most recently, his work includes using AI to understand investor behavior and market dynamics. His research has been published in top finance and accounting journals, including the Journal of Financial Economics, the Review of Financial Studies, and the Accounting Review, and mentioned by the Wall Street Journal, The Economist, and the Financial Times. He obtained a Ph.D. from Emory University and a BA from Bard College.
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