IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20180088.html
   My bibliography  Save this paper

A Time-Varying Parameter Model for Local Explosions

Author

Listed:
  • Francisco (F.) Blasques

    (VU Amsterdam)

  • Siem Jan (S.J.) Koopman

    (VU Amsterdam)

  • Marc Nientker

    (VU Amsterdam)

Abstract

Locally explosive behavior is observed in many economic and financial time series when bubbles are formed. We introduce a time-varying parameter model that is capable of describing this behavior in time series data. Our proposed model can be used to predict the emergence, existence and burst of bubbles. We adopt a flexible observation driven model specification that allows for different bubble shapes and behavior. We establish stationarity, ergodicity, and bounded moments of the data generated by our model. Furthermore, we obtain the consistency and asymptotic normality of the maximum likelihood estimator. Given the parameter estimates, our filter is capable of extracting the unobserved bubble process from observed data. We study finite-sample properties of our estimator through a Monte Carlo simulation study. Finally, we show that our model compares well with noncausal models in a financial application concerning the Bitcoin/US dollar exchange rate.

Suggested Citation

  • Francisco (F.) Blasques & Siem Jan (S.J.) Koopman & Marc Nientker, 2018. "A Time-Varying Parameter Model for Local Explosions," Tinbergen Institute Discussion Papers 18-088/III, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20180088
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/18088.pdf
    Download Restriction: no
    ---><---

    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. Xi Chen & Michael Funke, 2013. "Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles," National Institute Economic Review, National Institute of Economic and Social Research, vol. 223(1), pages 39-48, February.
    3. Zhiguo He & Arvind Krishnamurthy, 2019. "A Macroeconomic Framework for Quantifying Systemic Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(4), pages 1-37, October.
    4. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    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. Olivier J. Blanchard & Mark W. Watson, 1982. "Bubbles, Rational Expectations and Financial Markets," NBER Working Papers 0945, National Bureau of Economic Research, Inc.
    8. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464.
    9. Diba, Behzad T & Grossman, Herschel I, 1988. "Explosive Rational Bubbles in Stock Prices?," American Economic Review, American Economic Association, vol. 78(3), pages 520-530, June.
    10. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    11. Francisco (F.) Blasques & Marc Nientker, 2017. "A Stochastic Recurrence Equation Approach to Stationarity and phi-Mixing of a Class of Nonlinear ARCH Models," Tinbergen Institute Discussion Papers 17-072/III, Tinbergen Institute.
    12. Phillips, Peter C.B. & Shi, Shu-Ping, 2018. "Financial Bubble Implosion And Reverse Regression," Econometric Theory, Cambridge University Press, vol. 34(4), pages 705-753, August.
    13. 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.
    14. Shi, Shuping, 2017. "Speculative bubbles or market fundamentals? An investigation of US regional housing markets," Economic Modelling, Elsevier, vol. 66(C), pages 101-111.
    15. 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.
    16. Fries, Sébastien & Zakoian, Jean-Michel, 2019. "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
    17. Peter C. B. Phillips & Shuping Shi, 2019. "Detecting Financial Collapse and Ballooning Sovereign Risk," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(6), pages 1336-1361, December.
    18. 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.
    19. Matthew S. Yiu & Lu Jin, 2012. "Detecting Bubbles in the Hong Kong Residential Property Market: An Explosive-Pattern Approach," Working Papers 012012, Hong Kong Institute for Monetary Research.
    20. Yiu, Matthew S. & Yu, Jun & Jin, Lu, 2013. "Detecting bubbles in Hong Kong residential property market," Journal of Asian Economics, Elsevier, vol. 28(C), pages 115-124.
    21. George Milunovich & Shuping Shi & David Tan, 2019. "Bubble detection and sector trading in real time," Quantitative Finance, Taylor & Francis Journals, vol. 19(2), pages 247-263, February.
    22. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2014. "Bubbles in food commodity markets: Four decades of evidence," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 129-155.
    23. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
    24. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    25. Luciano Gutierrez, 2013. "Speculative bubbles in agricultural commodity markets-super- †," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(2), pages 217-238, 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. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    2. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    3. Xuanling Yang & Dong Li & Ting Zhang, 2024. "A simple stochastic nonlinear AR model with application to bubble," Papers 2401.07038, arXiv.org.

    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. Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023. "Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers 23-065/III, Tinbergen Institute.
    2. Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
    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. Caravello, Tomas E. & Psaradakis, Zacharias & Sola, Martin, 2023. "Rational bubbles: Too many to be true?," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    5. 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.
    6. Li, Zheng-Zheng & Su, Chi-Wei & Chang, Tsangyao & Lobonţ, Oana-Ramona, 2022. "Policy-driven or market-driven? Evidence from steam coal price bubbles in China," Resources Policy, Elsevier, vol. 78(C).
    7. Shuping Shi & Peter C.B. Phillips, 2023. "Diagnosing housing fever with an econometric thermometer," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 159-186, February.
    8. 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.
    9. 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.
    10. Wei-Fong Pan, 2019. "Detecting bubbles in China’s regional housing markets," Empirical Economics, Springer, vol. 56(4), pages 1413-1432, April.
    11. Shuping Shi & Peter C. B. Phillips, 2022. "Econometric Analysis of Asset Price Bubbles," Cowles Foundation Discussion Papers 2331, Cowles Foundation for Research in Economics, Yale University.
    12. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    13. Janusz Sobieraj & Dominik Metelski, 2021. "Testing Housing Markets for Episodes of Exuberance: Evidence from Different Polish Cities," JRFM, MDPI, vol. 14(9), pages 1-29, September.
    14. Roselyne Joyeux & George Milunovich, 2015. "Speculative bubbles, financial crises and convergence in global real estate investment trusts," Applied Economics, Taylor & Francis Journals, vol. 47(27), pages 2878-2898, June.
    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. 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.
    17. 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.
    18. Rafiq Ahmed & Syed Tehseen Jawaid & Samina Khalil, 2021. "Bubble Detection in Housing Market: Evidence From a Developing Country," SAGE Open, , vol. 11(2), pages 21582440211, April.
    19. Wen-Yi Chen & Yia-Wun Liang & Yu-Hui Lin, 2016. "Is the United States in the middle of a healthcare bubble?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(1), pages 99-111, January.
    20. Cretí, Anna & Joëts, Marc, 2017. "Multiple bubbles in the European Union Emission Trading Scheme," Energy Policy, Elsevier, vol. 107(C), pages 119-130.

    More about this item

    Keywords

    bubbles; observation driven models; noncausal models; stationary; ergodic; consistency; asymptotic normality; exchange rates;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tin:wpaper:20180088. 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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    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.