Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-23T18:17:41.520Z Has data issue: false hasContentIssue false

SIGN-BASED UNIT ROOT TESTS FOR EXPLOSIVE FINANCIAL BUBBLES IN THE PRESENCE OF DETERMINISTICALLY TIME-VARYING VOLATILITY

Published online by Cambridge University Press:  29 March 2019

David I. Harvey*
Affiliation:
University of Nottingham
Stephen J. Leybourne
Affiliation:
University of Nottingham
Yang Zu
Affiliation:
University of Nottingham
*
*Address correspondence to David Harvey, School of Economics, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; e-mail: dave.harvey@nottingham.ac.uk.

Abstract

This article considers the problem of testing for an explosive bubble in financial data in the presence of time-varying volatility. We propose a sign-based variant of the Phillips, Shi, and Yu (2015, International Economic Review 56, 1043–1077) test. Unlike the original test, the sign-based test does not require bootstrap-type methods to control size in the presence of time-varying volatility. Under a locally explosive alternative, the sign-based test delivers higher power than the original test for many time-varying volatility and bubble specifications. However, since the original test can still outperform the sign-based one for some specifications, we also propose a union of rejections procedure that combines the original and sign-based tests, employing a wild bootstrap to control size. This is shown to capture most of the power available from the better performing of the two tests. We also show how a sign-based statistic can be used to date the bubble start and end points. An empirical illustration using Bitcoin price data is provided.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We are grateful to the Editor, Peter Phillips, the Co-Editor, Anna Mikusheva, and three anonymous referees for their very helpful and constructive comments.

References

REFERENCES

Beare, B.K. (2018) Unit root testing with unstable volatility. Journal of Time Series Analysis, 39, 816835.CrossRefGoogle Scholar
Blanchard, O.J. & Watson, M.W. (1982) Bubbles, rational expectations and financial markets. In Wachtel, P. (ed.), Crises in the Economic and Financial Structure, pp. 295316. Lexington Books.Google Scholar
Boldin, M.V. (2013). On qualitatively robust sign test in random walk model. Proceedings of the 10th International Conference ‘Computer Data Analysis and Modeling: Theoretical and Applied Stochastics’, Minsk, Volume 1, 194197.Google Scholar
Campbell, B. & Dufour, J.-M. (1995) Exact nonparametric orthogonality and random walk tests. Review of Economics and Statistics 77, 116.CrossRefGoogle Scholar
Campbell, J.Y., Lo, A.W.C., & MacKinlay, A.C. (1997) The Econometrics of Financial Markets. Princeton University Press.CrossRefGoogle Scholar
Christoffersen, P.F. (2012) Elements of Financial Risk Management, 2nd ed. Academic Press.Google Scholar
Gourieroux, C. & Jasiak, J. (2018) Robust analysis of the martingale hypothesis. Discussion Paper, York University, Canada.Google Scholar
Granger, C.W.J. & Swanson, N.R. (1997). An introduction to stochastic unit-root processes. Journal of Econometrics 80, 3562.CrossRefGoogle Scholar
Harvey, D.I., Leybourne, S.J., & Taylor, A.M.R. (2009) Unit root testing in practice: Dealing with uncertainty over the trend and initial condition (with commentaries and rejoinder). Econometric Theory 25, 587667.CrossRefGoogle Scholar
Harvey, D.I., Leybourne, S.J., Sollis, R., & Taylor, A.M.R. (2016) Tests for explosive financial bubbles in the presence of non-stationary volatility. Journal of Empirical Finance 38, 548574.CrossRefGoogle Scholar
Homm, U. & Breitung, J. (2012). Testing for speculative bubbles in stock markets: A comparison of alternative methods. Journal of Financial Econometrics 10, 198231.CrossRefGoogle Scholar
Phillips, P.C.B. & Magdalinos, T. (2007) Limit theory for moderate deviations from a unit root. Journal of Econometrics 136, 115130.CrossRefGoogle Scholar
Phillips, P.C.B. & Shi, S.-P. (2018a) Financial bubble implosion and reverse regression. Econometric Theory 34, 705753.CrossRefGoogle Scholar
Phillips, P.C.B. & Shi, S.-P. (2018b) Real Time Monitoring of Asset Markets: Bubbles and Crises. Discussion Paper.Google Scholar
Phillips, P.C.B., Shi, S.-P., & Yu, J. (2014) Specification sensitivity in right-tailed unit root testing for explosive behaviour. Oxford Bulletin of Economics and Statistics 76, 315333.CrossRefGoogle Scholar
Phillips, P.C.B., Shi, S.-P., & Yu, J. (2015) Testing for multiple bubbles: Historical episodes of exuberance and collapse in the S&P 500. International Economic Review 56, 10431077.CrossRefGoogle Scholar
Phillips, P.C.B., Wu, Y., & Yu, J. (2011) Explosive behavior in the 1990s Nasdaq: When did exuberance escalate stock values? International Economic Review 52, 201226.CrossRefGoogle Scholar
Rapach, D.E., Strauss, J.K., & Wohar, M.E. (2008) Forecasting stock return volatility in the presence of structural breaks. In Rapach, D.E. & Wohar, M.E. (eds.), Forecasting in the Presence of Structural Breaks and Model Uncertainty, Emerald Series Frontiers of Economics and Globalization, vol. 3, pp. 381416. Emerald.CrossRefGoogle Scholar
Shi, S.-P., Hurn, S., & Phillips, P.C.B. (2018a) Causal Change Detection in Possibly Integrated Systems: Revisiting the Money-Income Relationship. Discussion Paper.Google Scholar
Shi, S.-P., Phillips, P.C.B., & Hurn, S. (2018b) Change detection and the causal impact of the yield curve. Journal of Time Series Analysis 39, 966987.CrossRefGoogle Scholar
So, B.S. & Shin, D.W. (2001) An invariant sign test for random walks based on recursive median adjustment. Journal of Econometrics 102, 197229.CrossRefGoogle Scholar
Tsay, R.S. (2010) Analysis of Financial Time Series, 3rd ed. Wiley Series in Probability and Statistics. Wiley.CrossRefGoogle Scholar
Van der Vaart, A.W. (2000) Asymptotic Statistics. Cambridge University Press.Google Scholar