北京大学金融工程实验室
“金工首席谈量化”专题讲座
第26讲：经济周期与量化资产配置：理论、实证及应用
主讲人：陈烨（华泰证券金融工程策略指数组长）
主持老师：（北大经院）黎新平
时间：2024年5月14日（周二）19:00-21:30
形式：北京大学经济学院107会议室
主要内容：
此次讲座将讨论资产配置与经济金融周期的融合应用。华泰证券经过八年系统性研究，创新地将全球资产价格、宏观经济、工业体系数据纳入统一的研究框架内，定量观测纷繁复杂的经济变量背后所存在的42个月、100个月、200个月周期运行规律，并依此构建大类资产定量预测模型，使周期规律真正应用于投资实践。
主讲人简介：
陈烨，华泰证券研究所金融工程团队策略指数组长。北京大学计算数学博士、数学/经济学双学士。2016年开始从事金融工程研究，曾任职于建信基金，目前主要从事量化经济周期、宏观因子、大类资产配置策略指数等方向研究。
注1：讲座现场赠送华泰证券主办最新一期《中国量化投资季刊》，数量有限先到先得。
注2：本次讲座也将介绍华泰金工团队实习及招聘相关内容，欢迎同学们参加。
北大经院工作坊880场
Artificial Intelligence and Information Production in Selection Markets: Experimental Evidence from Insurance Intermediation
风险、保险与不确定性经济学工作坊
主讲人：刘行（清华大学五道口金融学院助理教授）
主持人：
（北大经院）贾若
（人大财金）陈泽
（清华经管）冯润桓
参与老师：
（北大经院）郑伟
（人大财金）魏丽
时间：2024年5月14日（周二）10：00-11：30
线上形式：腾讯会议
会议号：311 919 936
线下地点：北京大学经济学院302会议室
主讲人简介：
刘行博士现任清华大学五道口金融学院助理教授。他的研究方向包括公司金融、金融科技和保险市场。他的研究关注无形资产的经济价值，如公司文化、工作的非物质激励维度、知识产权、以及新技术对信息生产和代理冲突的影响。他的研究成果目前发表于Journal of Financial and Quantitative Analysis和Management Science。刘行博士于2023年获得加拿大英属哥伦比亚大学金融学博士学位。此前他在清华大学获得金融专业硕士学位，在中国人民大学财政金融学院保险系获得经济学学士学位。
摘要：
Selection markets create a multitasking environment where intermediary agents often need to increase consumer take-up as well as resolve information asymmetries about consumer expected cost during the sales process. I study how artificial intelligence (AI) affects attention allocation and information production in human-intermediated markets by analyzing a large-scale randomized experiment conducted by a top insurance agency in China. In the experiment, the firm provided treated agents with an AI-generated estimation of consumer demand for insurance, based on consumer digital footprints on the advertisements on social media; these footprints were available to all agents prior to the experiment. I show that AI demand prediction shifts agents' attention to converting high-intent consumers, improving agents' sales by 14%. As an unintended consequence, AI-generated demand information reduces agents' own information acquisition and increases adverse selection, consistent with attention models and a crowding out of risk information. Moreover, treated agents bring in riskier consumers but do not match them to more expensive products to achieve stronger incentive compatibility. The findings suggest that a common application of AI to predict consumer demand can have side effects on human information production, market efficiency, and can exacerbate agency conflicts when intermediary agents capitalize on AI.
北大经院工作坊881场
Hot and Crowded: Temperature, healthcare utilization and patient outcomes
经院-全健院
“健康与劳动经济学”工作坊
主讲人：Matthew Neidell (Professor, Health Policy and Management at Columbia University)
主持人：（北大全健院）潘聿航
参与老师：
（北大经院）秦雪征、石菊、姚奕、王耀璟、袁野、Kevin Devereux、梁远宁、庄晨
（北大全健院）刘国恩、黄成、孙宇、吕蓓妮、林淑君、杨佳楠、林昊翔、蒋少翔
时间：2024年5月15日（周三）21:00-22:30
形式:ZOOM会议
会议号：834 6363 4173
密码：416012
主讲人简介：
Matthew Neidell is a professor of economics at Columbia University in the Department of Health Policy and Management. Professor Neidell specializes in environmental, health, and labor economics. His most recent work applies the latest empirical methods to examine the relationship between the environment and a wide range of measures of well-being, including worker productivity, human capital, and decision making. Previous related work has focused on the effect of the environment on health outcomes and avoidance behavior.
摘要：
This study explores how temperature-induced hospital crowding influences care trajectories and patient outcomes. Utilizing comprehensive data from Mexico’s largest healthcare subsystem from 2012 to 2019, including emergency, inpatient, and outpatient visits, we delve into the impact of daily temperature shocks on healthcare service dynamics. Our findings reveal a linear increase in healthcare demand reaching a 10% uptick in emergency department visits in the hottest bin compared to average days. While more patients are admitted from ERs into hospitals, the likelihood of an individual patient's admission decreases as temperatures climb, suggesting a capacity crunch in healthcare facilities. This trend of increasing patient triage leads to more severe patients being sent home on hotter days. Furthermore, we observe a deterioration in care quality, reflected in heightened excess mortality rates inside hospitals. Data from death certificates confirm an overall increase in mortality on extreme days. Deaths outside hospitals, in particular, escalate more sharply. Our results shed light on the broader implications of climate-driven hospital crowding.
供稿：科研与博士后办公室
美编：芋圆
责编：度量、雨禾、雨田
