题目：Common Bubble  Detection in Large-Dimensional Financial Systems

报告人：陈烨副教授 (首都经济贸易大学)

时间：2020年06月18日（周四）上午10:00-11:30

报告方式：腾讯会议号193 862 061

摘要：Price bubbles in multiple assets are sometimes nearly coincident in  occurrence. Such near-coincidence is strongly suggestive of co-movement in the  associated asset prices and likely driven by certain factors that are latent in  the financial or economic system with common effects across several markets. Can  we detect the presence of such common factors at the early stages of their  emergence? To answer this question, we build a factor model that includes both  I(1) and mildly explosive factors to capture normal and exuberant phases in such  phenomena. The I(1) factor models the primary driving force of market  fundamentals. The explosive factor models latent forces that underlie the  formation of asset price bubbles, which typically exist only for subperiods of  the sample. The paper provides an algorithm for testing the presence of and  date-stamping the origination of price bubbles determined by latent factors in a  large-dimensional system embodying many markets. Asymptotics of the bubble test  statistic are given under the null of no common bubbles and the alternative of a  common bubble across these markets. We prove consistency of a factor bubble  detection process for the origination date of the common bubble. Simulations  show good finite sample performance of the testing algorithm in terms of its  successful detection rates. Our methods are applied to real estate markets  covering 89 major cities in China over the period January 2003 to March 2013.  Results suggest the presence of three common bubble episodes in what are known  as China’s Tier 1 and Tier 2 cities over the sample period. There appears to be  little evidence of a common bubble in Tier 3 cities.

报告人简介:

陈烨，2014年博士毕业于新加坡管理大学经济系，现任首都经济贸易大学国际经济管理学院副教授。主要研究领域为理论计量经济学，金融计量经济学，经济预测，并在计量经济学领域的国际顶级期刊Journal of Econometrics上发表多篇学术论文。