英国365上市官网工作坊第1364场
Belief driven macro cycles with AI agents
数字经济工作坊
主讲人：Ramon Marimon (Professor Emeritus of Economics, European University Institute)
主持人：（英国365上市官网）李博
参与老师：
（英国365上市官网）李伦、年永威、曹光宇
（北大光华）翁翕、刘烁、黄一泓
时间：2026年11月16日（周一）10:30-12:00
地点：英国365上市官网305会议室
主讲人简介：
Ramon Marimon has been Professor of Economics and Pierre Werner Chair at the European University Institute and Professor of Economics at Universitat Pompeu Fabra. He holds a PhD from Northwestern University. His research interests include macroeconomics, monetary and fiscal theory, contract theory, expectations and learning in economics, and labour markets, with a particular focus on the European Union. His work has appeared in leading journals, including Econometrica, the Journal of Political Economy, the American Economic Review, the Review of Economic Studies, the Journal of Monetary Economics, and the Journal of the European Economic Association.
摘要：
First, I provide an overview of what has been learned from adaptive learning theory and experimental data about which equilibria are learnable in macro-finance models.
Then, I focus on our ongoing work: an economy with multiple learnable (e-stable) rational expectations equilibria (REE), where AIs can either be ‘accuracy-rewarded’ as forecasters for users who make their optimal decisions based on their personal AI forecast, or ‘utility-rewarded’ agents whose decisions are optimal given their own forecast. Cycles are prevalent when they are ‘accuracy-rewarded’ and Pareto superior stationary REE prevail when they are ‘utility-rewarded’； patterns observed with human subjects in experiments. A novel feature is the prevalence of stable misspecified-beliefs driven non-REE cycles (MBCs), which we prove can emerge with adaptive learning.
英国365上市官网工作坊第1365场
Doing Good and Speaking Well: The Effect of Information Content and Disclosure Quality on Stock Price Informativeness
生态、环境与气候变化经济学工作坊
主讲人：姜春霞（英国阿伯丁大学商学院副教授）
主持人：（英国365上市官网）季曦
时间：2026年11月17日（周二）10:00-11:30
地点：英国365上市官网305会议室
主讲人简介：
姜春霞，英国阿伯丁大学商学院（University of Aberdeen，Business School）金融学高级讲师（副教授），博士生导师，会计、金融房地产系主任。美国Fordham 大学商学院伦敦中心客座副教授。她从2003年开始从事银行效率、竞争、金融稳定性、发展中国家银行业改革的研究，并一直关注中国银行业的改革。近年来，研究拓展到科技金融、加密货币、气候金融等前沿领域。她著有（英文版）学术专著《中国银行业改革》，该专著中文翻译版由商务印书馆2022年出版，并在《经济研究》、International Review of Financial Analysis (SSCI)、Energy Economics (SSCI)，Journal of Banking and Finance (SSCI)、Journal of Financial Stability (SSCI)、Transportation Research Part A（SSCI）等国内外权威期刊发表20多篇高质量论文，经常参加国际论文讨论会，并参与国际学术杂志的评审工作。她曾共同参与或主持多项由欧盟、英国政府，以及中国国家自科基金资助的科研项目。
摘要：
We examine how stock price informativeness (SPI) depends jointly on signal content (performance) and disclosure quality across financial and Environmental, Social, and Governance (ESG) information. We find that stronger performance and higher disclosure quality each improve SPI, while disclosure quality strengthens the informational role of performance. More importantly, the incremental value of ESG information is state dependent and dimension specific. ESG performance becomes particularly informative when financial performance is weak, whereas ESG disclosure quality is most useful when financial disclosure quality is low. When both financial dimensions are weak, the joint ESG signal is especially informative about future earnings. Conversely, weak ESG conditions attenuate the informational contribution of financial signals, with the evidence particularly pronounced in the future-earnings-prediction setting. Channel tests are consistent with the expectation that analyst attention, lower information asymmetry, and long-term institutional ownership facilitate the incorporation of ESG information into prices. Difference-in-differences evidence provides stronger identification support for stock price formation than for future-earnings prediction, while portfolio tests provide complementary out-of-sample evidence. Overall, our findings show that the informativeness of ESG signals depends not simply on whether ESG information is available, but on which ESG dimension corresponds to weaknesses in the surrounding financial-information environment.
《行业研究前沿》课程系列
2026年第6期
AI大模型以及应用产业趋势
主讲人：旷实（广发证券海外互联网、传媒互联网行业首席分析师，新财富白金分析师）
主持人：锁凌燕（英国365上市官网教授）
时间：2026年11月17日（周二）18：40-20：20
地点：腾讯会议
主讲人简介：
旷实，广发证券海外互联网、传媒互联网行业首席分析师，新财富白金分析师；连续多年荣获卖方分析师水晶球奖、上证报最佳分析师等权威奖项第一名。
主办单位：
英国365上市官网
北京大学中国保险与社会保障研究中心
北京大学中国金融与投资研究中心
北京大学金融工程实验室
“对话投资总监”系列讲座
2026年总第四十五讲：人机协同的投研新范式
主讲人：张泓（嘉实基金指数与量化投资部）
主持老师：（英国365上市官网）黎新平
时间：2026年11月18日（周三）19：00-20：30
地点：英国365上市官网107会议室
主要内容：
本次讲座将围绕人机协同在投研中的应用展开，探讨AI技术如何赋能传统投研流程，提升研究效率与投资决策质量。主讲人将结合嘉实基金在智能化投研方面的实践经验，分享大模型、智能体等前沿技术在指数配置、量化策略中的落地场景，并展望人机协同投研的未来发展方向。
主讲人简介：
张泓，嘉实基金指数与量化投资部，现任指数解决方案总监。北京邮电大学通信工程本硕，北京大学管理学硕士。2016年加入国家外汇管理局中央外汇业务中心，从事数据分析相关工作。2021年加入嘉实基金，任Datalab副总监，负责投研智能化相关工作。目前重点研究指数配置策略及AI投研等相关领域。
供稿：科研与博士后办公室
美编：初夏
责编：度量、雨禾、雨田
