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sidenav header background[5月27日] 计量金融与大数据分析workshop
发布日期：2022-05-23 12:21 来源：
A Model for Daily Global Stock Market Returns
主讲人：汤海涵（复旦大学）
主持人：（国发院）沈艳、黄卓、孙振庭、张俊妮
（北大新结构经济学研究院）胡博
（经济学院）王一鸣、王熙、刘蕴霆 、王法
时间：2022年5月27日（周五）10:00 AM -- 11:30 AM
腾讯会议：873-695-705
报告摘要：
Most stock markets are open for 6-8 hours per trading day. The Asian, European and American stock markets are separated in time by time-zone differences. We propose a statistical dynamic factor model for a large number of daily returns across multiple time zones. Our model has a common global factor as well as continental factors. Under a mild fixed-signs assumption, our model is identified and has a structural interpretation. We propose several estimators of our model: the maximum likelihood estimator-one day (MLE-one day), the quasi-maximum likelihood estimator (QMLE), QMLE-m (an improved estimator from QMLE), QMLE-res (similar to MLE-one day), and a Bayesian estimator (Gibbs sampling). We establish consistency, the rate of convergence and asymptotic distributions of QMLE and QMLE-m. We next provide the heuristic procedures for conducting inference for MLE-one day and QMLE-res. Monte Carlo simulations reveal that these estimators work well. We then apply our model to two real data sets: (1) the equity portfolio returns of Japan, Europe and US; (2) the MSCI equity indices of 41 developed and emerging markets. Some new insights about linkages between different markets are drawn.
主讲人简介：
汤海涵，复旦大学泛海国际金融学院金融学副教授。他的研究领域为计量经济理论，金融计量经济学，应用计量经济学。他的研究课题入选了2018年上海晨光计划，2019年上海浦江人才项目，和2019年国家自然科学委员会青年科学基金项目。他的论文还在国际知名期刊 Journal of Econometrics 和 Econometric Theory上发表。汤海涵教授于2017年获得剑桥大学经济学博士学位，2012年获得剑桥大学经济研究硕士学位，2011年获得伦敦政治经济学院计量经济和数理经济学士学位。
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首页
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教学项目展开 / 收起
sidenav background教学项目
sidenav header background[5月27日] 计量金融与大数据分析workshop
发布日期：2022-05-23 12:21 来源：
A Model for Daily Global Stock Market Returns
主讲人：汤海涵（复旦大学）
主持人：（国发院）沈艳、黄卓、孙振庭、张俊妮
（北大新结构经济学研究院）胡博
（经济学院）王一鸣、王熙、刘蕴霆 、王法
时间：2022年5月27日（周五）10:00 AM -- 11:30 AM
腾讯会议：873-695-705
报告摘要：
Most stock markets are open for 6-8 hours per trading day. The Asian, European and American stock markets are separated in time by time-zone differences. We propose a statistical dynamic factor model for a large number of daily returns across multiple time zones. Our model has a common global factor as well as continental factors. Under a mild fixed-signs assumption, our model is identified and has a structural interpretation. We propose several estimators of our model: the maximum likelihood estimator-one day (MLE-one day), the quasi-maximum likelihood estimator (QMLE), QMLE-m (an improved estimator from QMLE), QMLE-res (similar to MLE-one day), and a Bayesian estimator (Gibbs sampling). We establish consistency, the rate of convergence and asymptotic distributions of QMLE and QMLE-m. We next provide the heuristic procedures for conducting inference for MLE-one day and QMLE-res. Monte Carlo simulations reveal that these estimators work well. We then apply our model to two real data sets: (1) the equity portfolio returns of Japan, Europe and US; (2) the MSCI equity indices of 41 developed and emerging markets. Some new insights about linkages between different markets are drawn.
主讲人简介：
汤海涵，复旦大学泛海国际金融学院金融学副教授。他的研究领域为计量经济理论，金融计量经济学，应用计量经济学。他的研究课题入选了2018年上海晨光计划，2019年上海浦江人才项目，和2019年国家自然科学委员会青年科学基金项目。他的论文还在国际知名期刊 Journal of Econometrics 和 Econometric Theory上发表。汤海涵教授于2017年获得剑桥大学经济学博士学位，2012年获得剑桥大学经济研究硕士学位，2011年获得伦敦政治经济学院计量经济和数理经济学士学位。
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