Volume 56, Issue 4
Original Article

TESTING FOR MULTIPLE BUBBLES: HISTORICAL EPISODES OF EXUBERANCE AND COLLAPSE IN THE S&P 500

Peter C. B. Phillips

Yale University, U.S.A., University of Auckland, New Zealand, University of Southampton, U.K., and Singapore Management University, Singapore; Macquarie University and CAMA, Australia, Singapore Management University, Singapore

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Shuping Shi

Yale University, U.S.A., University of Auckland, New Zealand, University of Southampton, U.K., and Singapore Management University, Singapore; Macquarie University and CAMA, Australia, Singapore Management University, Singapore

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Jun Yu

Yale University, U.S.A., University of Auckland, New Zealand, University of Southampton, U.K., and Singapore Management University, Singapore; Macquarie University and CAMA, Australia, Singapore Management University, Singapore

This article and its technical companion “Testing for Multiple Bubbles: Limit Theory of Real Time Detectors” (Phillips et al., 2015a, this issue) build on work that was originally circulated in 2011 in a long paper entitled “Testing for Multiple Bubbles” accompanied by a long supplement of technical results. We are grateful to the editor and three referees for helpful comments, as well as many colleagues, seminar participants, and central bank economists for valuable discussions. Phillips acknowledges support from the NSF under grant numbers SES 09‐56687 and SES 12‐58258. Shi acknowledges the Financial Integrity Research Network (FIRN) for funding support. Yu acknowledges support from the Singapore Ministry of Education for Academic Research Fund under grant number MOE2011‐T2‐2‐096. Please address correspondence to: Peter C. B. Phillips, Cowles Foundation for Research in Economics, Yale University, Box 208281, New Haven, CT 06520‐8281, U.S.A. E‐mail: peter.phillips@yale.edu.

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First published: 28 October 2015
Citations: 307

Abstract

Recent work on econometric detection mechanisms has shown the effectiveness of recursive procedures in identifying and dating financial bubbles in real time. These procedures are useful as warning alerts in surveillance strategies conducted by central banks and fiscal regulators with real‐time data. Use of these methods over long historical periods presents a more serious econometric challenge due to the complexity of the nonlinear structure and break mechanisms that are inherent in multiple‐bubble phenomena within the same sample period. To meet this challenge, this article develops a new recursive flexible window method that is better suited for practical implementation with long historical time series. The method is a generalized version of the sup augmented Dickey–Fuller (ADF) test of Phillips et al. (“Explosive behavior in the 1990s NASDAQ: When did exuberance escalate asset values?” International Economic Review 52 (2011), 201–26; PWY) and delivers a consistent real‐time date‐stamping strategy for the origination and termination of multiple bubbles. Simulations show that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. An empirical application of the methodology is conducted on S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach successfully identifies the well‐known historical episodes of exuberance and collapses over this period, whereas the strategy of PWY and a related cumulative sum (CUSUM) dating procedure locate far fewer episodes in the same sample range.

Number of times cited according to CrossRef: 307

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