Jinglin Luojia Finance Seminar: Spring Corporate Finance Workshop, 2021

日期：2021年6月5日（星期六）

场地：B249

主办单位： 武汉大学经济与管理学院金融系

            武汉大学金融科技研究中心

            武汉大学大数据研究院金融大数据研究中心

议程
9:00 – 9:50	1. Institutional Investors and Corporate Environmental Innovation 报告人：崔静波，昆山杜克大学
9:50 – 10:40	2. Information Acquisition and Usage of Retail Investors: Evidence from Web Views and Watchlists 报告人：贾越珵，中央财经大学
10:40 – 11:00	茶歇
11:00 – 11:50	3. Superstition and the Stock Market: Evidence from Lunar Bogey 报告人：李安泰，华中科技大学
11:50 – 14:00	午餐：珞珈山庄
14:00 – 14:50	4. Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets? 报告人：谢天，上海财经大学
14:50 – 15:40	5. Do Mobile Payment Platforms Compete with Each Other? Evidence from a Bank in China 报告人：陈国栋，上海纽约大学
15:40 – 16:00	茶歇
16:00 – 16:50	6. The gender gap in financial distress 报告人：周洋，武汉大学
	晚餐：TBD

二、报告人及文章摘要

1.崔静波

个人简介：崔静波，昆山杜克大学社会科学部和环境研究中心应用经济学副教授。曾担任武汉大学经济与管理学院副教授，美国爱荷华州立大学经济学系博士后、访问助理教授。博士毕业于美国爱荷华州立大学获经济学博士学位，硕士和本科分别毕业于武汉大学和华中科技大学。研究方向：环境经济学、公司金融、专利创新、国际贸易。研究成果已发表在经济学国内顶级期刊《经济研究》、《管理世界》、《经济学（季刊）》、《中国工业经济》，以及国际权威期刊American Economic Review Papers and Proceedings, Journal of Environmental Economics and Management, American Journal of Agricultural Economics, China Economic Review, The World Economy, Energy Economics, Energy Policy等。主持国家自然科学基金面上项目、青年项目、应急项目、以及江苏省青蓝项目。长期担任环境经济学、农业经济学、创新经济学国际顶级学术期刊(JEEM, JAERE, AJAE, Nature Climate Change, Research Policy)，以及国内权威学术期刊《中国工业经济》、《经济学（季刊）》等匿名审稿人。

题目：Institutional Investors and Corporate Environmental Innovation

摘要：This paper addresses whether institutional investors drive the innovation direction of corporates toward environmentally friendly technologies. Using environmental patents filed by Chinese publicly-listed firms in the manufacturing and public utility sectors during the 2003-2016 period, we find the positive relationship between shareholding ratios of institutional investors and corporate environmental innovation. Institutional investors lead to a higher ratio of environmental patents in total patents for corporates in the pollution-intensive sector than those in the non-pollution-intensive sector. Institutional investors exert the roles of financial support and corporate governance in pursuit of monitoring corporate’s long-term sustainable innovation. Lastly, institutional investors are motivated by financial returns. They experience a higher return on corporate market value from the induced environmental innovation.

 

2.贾越珵

个人简介：贾越珵，中央财经大学中国金融发展研究院副教授，主要研究领域为实证资产定价、行为金融、机器学习。论文曾发表于Financial Management, Pacific-Basin Finance Journal, European Financial Management, The Financial Review, Review of Quantitative Finance and Accounting, Finance Research Letters。

题目：Information Acquisition and Usage of Retail Investors: Evidence from Web Views and Watchlists

摘要：We use a novel large data set of Chinese retail investors to study their information acquisition and usage activities. On the one hand, retail investors are more likely to collect information of attention-grabbing stocks, consistent with the view that they are unsophisticated. On the other hand, retail investors appear to utilize information with discretion in making investment decisions, consistent with the view that they have skills. Stocks that are selected more often following information acquisition by retail investors tend to be easier-to-value, have good future news, and earn higher returns even after controlling for stock characteristics.

 

3.李安泰

个人简介：华中科技大学管理学院财务金融系讲师，硕士生导师，加拿大特许专业会计师（CPA Canada），现任管理学院国际事务办主任。2018年博士毕业于华中科技大学管理学院，同年留校任教。曾赴美国宾夕法尼亚大学、英国剑桥大学和加拿大麦吉尔大学交流学习，研究领域包括文化与金融、大数据与科技金融、企业社会责任会计等。在Emerging Market Review, Pacific-Basin Finance Journal等期刊发表多篇论文。他获得2020年华中科技大学教学竞赛一等奖，华中科技大学优秀教师班主任等荣誉。

题目：Superstition and the Stock Market: Evidence from Lunar Bogey

摘要：Superstition affects investors’ cognition, judgment, and investment behavior. We utilize the traditional Chinese Almanac to construct the Lunar Bogey Index (LBI). Results show abnormal returns in stock markets associated with the LBI. This superstition effect is stronger in stocks with a higher limit of arbitrage and during bear-market periods and remains robust to diagnostic tests. The data are consistent with investors’ psychological biases in trading activities.

 

4.谢天

个人简介：谢天，曾获加拿大皇后大学博士学位。上海财经大学商学院世经国贸系副教授。主要研究方向为组合预测和模型平均，大数据分析，金融波动率预测等。主持和参与多项国家自然科学基金项目。研究成果在Management Science, Review of Economics and Statistics, Journal of Financial Econometric，Journal of Empirical Finance等期刊发表。

题目：Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets?

摘要：This paper first provides an illustration of the benefits of using machine learning for forecasting relative to traditional econometric strategies. We consider the short-term volatility of Bitcoin market by realized volatility observations. Our analysis highlights the importance of accounting for nonlinearities to explain the gains of machine learning algorithms and examines the robustness of our findings to the selection of hyperparameters. This provides an illustration of how different machine learning estimators improve the development of forecast models by relaxing the functional form assumptions that are made explicit when writing up an econometric model. Our second contribution is to illustrate how deep learning can be used to measure market level sentiment from a 10% random sample of Twitter users. This sentiment variable significantly improves forecast accuracy for every econometric estimator and machine algorithm considered in our forecasting application. This provides an illustration of the benefits of new tools from the natural language processing literature at creating variables that can improve the accuracy of forecasting models.

 

5.陈国栋

个人简介：Guodong Chen is an Assistant Professor of Finance, NYU Shanghai; Global Network Assistant Professor, NYU. Prior to joining NYU Shanghai, he was a PhD candidate at University of Michigan. He holds a PhD and dual MA degrees from University of Michigan, an MA degree from Peking University, and a BS degree from University of Science and Technology of China. His main research interests include consumer finance, household finance, banking and financial intermediations and behavioral finance.

题目：Do Mobile Payment Platforms Compete with Each Other? Evidence from a Bank in China

摘要：This paper estimates the effect of additional mobile payment access on spending patterns among Consumers in China. Based on a unique dataset of users’ credit card transactions from a large foreign bank in China, we find that new mobile payment users’ monthly consumption frequency increases by 3.75 percent relative to existing users when a prominent mobile payment method, WeChat Pay, is introduced to customers. We also find that the increase in consumption mainly occurs in low-value durables goods. Moreover, after investigating potential impacts on different payment channels, we find that the newly added WeChat Pay serves as a substitute to physical cards but a complement to other mobile payment methods.

 

6.周洋

个人简介：周洋，武汉大学经济与管理学院金融系副教授。主要研究领域为家庭金融。周洋老师2014年毕业于荷兰蒂尔堡大学，获金融学博士学位。在Journal of Financial and Quantitative Analysis, Journal of Economic Behavior and Organization, Journal of Banking and Finance，Journal of Futures Market等国际著名金融学杂志上发表论文7篇。讲授课程包括家庭金融学、金融市场学、投资学等。

题目：The gender gap in financial distress

摘要：We examine the gender gap in personal financial distress in the United States. Using a representative sample of households, we find that women are 39.95% more likely to default on debt payments, 37.58% more to default on bill payments, and 30.63% more to experience foreclosure, repossession, or bankruptcy than men. We provide evidence that susceptibility to adverse income shocks and suboptimal financial choices are two underlying mechanisms, with the latter accounting for a higher proportion in the identified gender gap than the former. We mitigate endogeneity concerns by controlling for sibling fixed effects.