IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v46y2022ipas154461232100369x.html
   My bibliography  Save this article

How to identify the different phases of stock market bubbles statistically?

Author

Listed:
  • Horváth, Lajos
  • Li, Hemei
  • Liu, Zhenya

Abstract

Eugene Fama once mentioned in 2016 that people have not come up with ways of identifying bubbles statistically. This paper presents the nonparametric change-point method to identify different stages of stock bubbles, and we derive its asymptotic distribution under the null hypothesis. By simulation, we obtain the corresponding critical value. In the empirical analysis, we employ this test and binary segmentation method to the 1990s Nasdaq bubble and get the same result as Phillips et al. (2011). We also apply this test to the S&P 500 index, the Shanghai stock index, the Nikkei 225 index, the FTSE 100 index, and the CAC 40 index respectively, and successfully identify the bubbles’ different phases in each stock market.

Suggested Citation

  • Horváth, Lajos & Li, Hemei & Liu, Zhenya, 2022. "How to identify the different phases of stock market bubbles statistically?," Finance Research Letters, Elsevier, vol. 46(PA).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pa:s154461232100369x
    DOI: 10.1016/j.frl.2021.102366
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461232100369X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.102366?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1043-1078, November.
    2. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "Sequential monitoring for changes from stationarity to mild non-stationarity," Journal of Econometrics, Elsevier, vol. 215(1), pages 209-238.
    3. Philipp Sibbertsen & Robinson Kruse, 2009. "Testing for a break in persistence under long‐range dependencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, May.
    4. Philipp Sibbertsen & Juliane Willert, 2012. "Testing for a break in persistence under long-range dependencies and mean shifts," Statistical Papers, Springer, vol. 53(2), pages 357-370, May.
    5. Peter C. B. Phillips & Jun Yu, 2011. "Dating the timeline of financial bubbles during the subprime crisis," Quantitative Economics, Econometric Society, vol. 2(3), pages 455-491, November.
    6. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    7. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert & Taylor, A.M. Robert, 2016. "Tests for explosive financial bubbles in the presence of non-stationary volatility," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 548-574.
    8. Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2020. "Date-stamping multiple bubble regimes," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 226-246.
    9. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1043-1078, November.
    10. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    11. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert, 2017. "Improving the accuracy of asset price bubble start and end date estimators," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 121-138.
    12. Evans, George W, 1991. "Pitfalls in Testing for Explosive Bubbles in Asset Prices," American Economic Review, American Economic Association, vol. 81(4), pages 922-930, September.
    13. Kenneth D. West, 1987. "A Specification Test for Speculative Bubbles," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(3), pages 553-580.
    14. Cunado, J. & Gil-Alana, L.A. & de Gracia, F. Perez, 2005. "A test for rational bubbles in the NASDAQ stock index: A fractionally integrated approach," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2633-2654, October.
    15. Froot, Kenneth A & Obstfeld, Maurice, 1991. "Intrinsic Bubbles: The Case of Stock Prices," American Economic Review, American Economic Association, vol. 81(5), pages 1189-1214, December.
    16. Lajos Horváth & William Pouliot & Shixuan Wang, 2017. "Detecting at-Most-m Changes in Linear Regression Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 552-590, July.
    17. Diba, Behzad T & Grossman, Herschel I, 1988. "The Theory of Rational Bubbles in Stock Prices," Economic Journal, Royal Economic Society, vol. 98(392), pages 746-754, September.
    18. Linton,Oliver, 2019. "Financial Econometrics," Cambridge Books, Cambridge University Press, number 9781107177154.
    19. Koustas, Zisimos & Serletis, Apostolos, 2005. "Rational bubbles or persistent deviations from market fundamentals?," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2523-2539, October.
    20. Demetrescu, Matei & Kuzin, Vladimir & Hassler, Uwe, 2008. "Long Memory Testing In The Time Domain," Econometric Theory, Cambridge University Press, vol. 24(1), pages 176-215, February.
    21. Hamilton, James D. & Whiteman, Charles H., 1985. "The observable implications of self-fulfilling expectations," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 353-373, November.
    22. LeRoy, Stephen F & Porter, Richard D, 1981. "The Present-Value Relation: Tests Based on Implied Variance Bounds," Econometrica, Econometric Society, vol. 49(3), pages 555-574, May.
    23. Górecki, Tomasz & Horváth, Lajos & Kokoszka, Piotr, 2018. "Change point detection in heteroscedastic time series," Econometrics and Statistics, Elsevier, vol. 7(C), pages 63-88.
    24. Kim, Jae-Young, 2000. "Detection of change in persistence of a linear time series," Journal of Econometrics, Elsevier, vol. 95(1), pages 97-116, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Potrykus, Marcin, 2023. "Investing in wine, precious metals and G-7 stock markets – A co-occurrence analysis for price bubbles," International Review of Financial Analysis, Elsevier, vol. 87(C).
    2. Aktham Maghyereh & Hussein Abdoh, 2022. "Bubble contagion effect between the main precious metals," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 40(1), pages 43-63, March.
    3. Li, Boyan & Diao, Xundi, 2023. "Structural break in different stock index markets in China," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    4. Ye Chen & Jian Li & Qiyuan Li, 2023. "Seemingly Unrelated Regression Estimation for VAR Models with Explosive Roots," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 910-937, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuchao Fan, 2022. "Dissecting the dot-com bubble in the 1990s NASDAQ," Papers 2206.14130, arXiv.org, revised Jul 2022.
    2. Michael Frömmel & Robinson Kruse, 2012. "Testing for a rational bubble under long memory," Quantitative Finance, Taylor & Francis Journals, vol. 12(11), pages 1723-1732, November.
    3. Efthymios Pavlidis & Alisa Yusupova & Ivan Paya & David Peel & Enrique Martínez-García & Adrienne Mack & Valerie Grossman, 2016. "Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun," The Journal of Real Estate Finance and Economics, Springer, vol. 53(4), pages 419-449, November.
    4. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2016. "Non-linearities in financial bubbles: Theory and Bayesian evidence from S&P500," Journal of Financial Stability, Elsevier, vol. 24(C), pages 61-70.
    5. Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
    6. Zhao, Yanping & Chang, Hsu-Ling & Su, Chi-Wei & Nian, Rui, 2015. "Gold bubbles: When are they most likely to occur?," Japan and the World Economy, Elsevier, vol. 34, pages 17-23.
    7. Balcilar, Mehmet & Gupta, Rangan & Jooste, Charl & Wohar, Mark E., 2016. "Periodically collapsing bubbles in the South African stock market," Research in International Business and Finance, Elsevier, vol. 38(C), pages 191-201.
    8. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    9. Martínez-García, Enrique & Grossman, Valerie, 2020. "Explosive dynamics in house prices? An exploration of financial market spillovers in housing markets around the world," Journal of International Money and Finance, Elsevier, vol. 101(C).
    10. Leone, Vitor & de Medeiros, Otavio Ribeiro, 2015. "Signalling the Dotcom bubble: A multiple changes in persistence approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 77-86.
    11. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Scientific Monographs, Bank of Finland, number 2012_047.
    12. Tolhurst, Tor N., 2018. "A Model-Free Bubble Detection Method: Application to the World Market for Superstar Wines," 2018 Annual Meeting, August 5-7, Washington, D.C. 274387, Agricultural and Applied Economics Association.
    13. Sharma, Shahil & Escobari, Diego, 2018. "Identifying price bubble periods in the energy sector," Energy Economics, Elsevier, vol. 69(C), pages 418-429.
    14. Gutierrez, Luciano, 2011. "Bootstrapping asset price bubbles," Economic Modelling, Elsevier, vol. 28(6), pages 2488-2493.
    15. Su, Chi-Wei & Li, Zheng-Zheng & Chang, Hsu-Ling & Lobonţ, Oana-Ramona, 2017. "When Will Occur the Crude Oil Bubbles?," Energy Policy, Elsevier, vol. 102(C), pages 1-6.
    16. repec:zbw:bofism:2012_047 is not listed on IDEAS
    17. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_047.
    18. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    19. Su, Chi-Wei & Wang, Kai-Hua & Chang, Hsu-Ling & Dumitrescu–Peculea, Adelina, 2017. "Do iron ore price bubbles occur?," Resources Policy, Elsevier, vol. 53(C), pages 340-346.
    20. Tie-Ying Liu & Hsu-Ling Chang & Chi-Wei Su & Xu-Zhao Jiang, 2016. "China's housing bubble burst?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(2), pages 361-389, April.
    21. Refet S. Gürkaynak, 2008. "Econometric Tests Of Asset Price Bubbles: Taking Stock," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 166-186, February.

    More about this item

    Keywords

    Change-point analysis; Weak-dependence assumption; Phases of stock market bubbles;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:46:y:2022:i:pa:s154461232100369x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.