Testing for Multiple Bubbles

By Peter C. B. Phillips, Shuping Shi, Jun Yu. 2011

169 citations recorded by the source corpus.

Identifying and dating explosive bubbles when there is periodically collapsing behavior over time has been a major concern in the economics literature and is of great importance for practitioners. The complexity of the nonlinear structure inherent in multiple bubble phenomena within the same sample period makes econometric analysis particularly difficult. The present paper develops new recursive procedures for practical implementation and surveillance strategies that may be employed by central banks and fiscal regulators. We show how the testing procedure and dating algorithm of Phillips, Wu and Yu (2011, PWY) are affected by multiple bubbles and may fail to be consistent. The present paper proposes a generalized version of the sup ADF test of PWY to address this difficulty, derives its asymptotic distribution, introduces a new date-stamping strategy for the origination and termination of multiple bubbles, and proves consistency of this dating procedure. Simulations show that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. Empirical applications are conducted to S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach identifies many key historical episodes of exuberance and collapse over this period, whereas the strategy of PWY and the CUSUM procedure locate far fewer episodes in the same sample range.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/78e3029bf41a3d41f02c2d1b87a545a73365c4ac

Citations in the corpus

• A systematic review of the bubble dynamics of cryptocurrency prices (2020, unknown): “…bubbles in the markets for cryptocurrencies, Cheung et al. [2015] use daily Bitcoin data over the period from July 17, 2010 to February 18, 2014 and adopt the Phillips et al. [2012] methodology in order to examine whether price bubbles exist in Bitcoin’s biggest exchange up to then, the Mt. Gox.”
• From Hero to Zero: Evidence of Performance Reversal and Speculative Bubbles in German Renewable Energy Stocks (2013, unknown): “…í µí±’ ] corresponds to the origination date and í µí¼̂ í µí±“ = �í µí±‡í µí±Ÿ̂ í µí±“ � to the collapse date of explosive price behavior, we compute estimates of these dates as in Phillips et al. (2011): í µí±Ÿ̂ í µí±’ = inf í µí± ≥í µí±Ÿ 0 {í µí± : í µí°´í µí°·í µí°¹ í µí± > í µí±í µí±£(í…”
• Bubbles in food commodity markets: Four decades of evidence ☆ (2014, unknown): “These results were obtained by applying the multiple bubble testing procedure of Phillips, Shi, and Yu (2012) to daily price sequences for individual futures contracts.”
• Dating the Timeline of Financial Bubbles During the Subprime Crisis (2011, unknown): “See Phillips, Shi, and Yu (2011).”
• Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun (2016, unknown): “Moreover, Phillips et al. (2012) show that such procedures can result in severe size distortions, and a reduction in power of both the SADF and GSADF tests.”