题目：Common Bubble Detection in Large-Dimensional Financial Systems
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.
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。