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Improving the accuracy of asset price bubble start and end date estimators

Harvey, David I.; Leybourne, Stephen J.; Sollis, Robert

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Authors

DAVID HARVEY dave.harvey@nottingham.ac.uk
Professor of Econometrics

Robert Sollis



Abstract

Recent research has proposed using recursive right-tailed unit root tests to date the start and end of asset price bubbles. In this paper an alternative approach is proposed that utilises model-based minimum sum of squared residuals estimators combined with Bayesian Information Criterion model selection. Conditional on the presence of a bubble, the dating procedures suggested are shown to offer consistent estimation of the start and end dates of a fixed magnitude bubble, and can also be used to distinguish between different types of bubble process, i.e. a bubble that does or does not end in collapse, or a bubble that is ongoing at the end of the sample. Monte Carlo simulations show that the proposed dating approach out-performs the recursive unit root test methods for dating periods of explosive autoregressive behaviour in finite samples, particularly in terms of accurate identification of a bubble's end point. An empirical application involving Nasdaq stock prices is discussed.

Citation

Harvey, D. I., Leybourne, S. J., & Sollis, R. (in press). Improving the accuracy of asset price bubble start and end date estimators. Journal of Empirical Finance, 40, https://doi.org/10.1016/j.jempfin.2016.11.001

Journal Article Type Article
Acceptance Date Nov 4, 2016
Online Publication Date Nov 9, 2016
Deposit Date Nov 10, 2016
Publicly Available Date Nov 10, 2016
Journal Journal of Empirical Finance
Print ISSN 0927-5398
Electronic ISSN 1879-1727
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 40
DOI https://doi.org/10.1016/j.jempfin.2016.11.001
Keywords Rational bubble; Explosive autoregression; Regime change; Break date estimation
Public URL https://nottingham-repository.worktribe.com/output/829473
Publisher URL http://www.sciencedirect.com/science/article/pii/S0927539816301219
Contract Date Nov 10, 2016

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