Professor DAVID HARVEY dave.harvey@nottingham.ac.uk
PROFESSOR OF ECONOMETRICS
Improving the accuracy of asset price bubble start and end date estimators
Harvey, David I.; Leybourne, Stephen J.; Sollis, Robert
Authors
Professor STEVE LEYBOURNE steve.leybourne@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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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
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