IDEAS home Printed from https://ideas.repec.org/a/wsi/afexxx/v13y2018i02ns2010495218500070.html
   My bibliography  Save this article

A Note On The Lse Of Three-Regime Tar Model With An Infinite Variance

Author

Listed:
  • YAXING YANG

    (Xiamen University and Hong Kong University of Science and Technology, P. R. China)

  • SHIQING LING

    (Xiamen University and Hong Kong University of Science and Technology, P. R. China)

Abstract

The least square estimator (LSE) of three-regime TAR models has been well developed when the noise has a finite variance. However, little is known about the asymptotic behavior of the LSE of three-regime threshold autoregressive (TAR) models in the heavy-tailed setting and neither theory nor methodology is available for model fitting in this case. In this paper, we use simulation method to study the asymptotic behavior of the LSE of infinite variance three-regime TAR models. A real example is given for the NASDAQ daily volume from the year 2012 to 2014. The results in this paper may provide an empirical insight for further theoretical research of the LSE of three-regime TAR models with heavy-tailed innovations.

Suggested Citation

  • Yaxing Yang & Shiqing Ling, 2018. "A Note On The Lse Of Three-Regime Tar Model With An Infinite Variance," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-13, June.
    • Handle: RePEc:wsi:afexxx:v:13:y:2018:i:02:n:s2010495218500070
    DOI: 10.1142/S2010495218500070
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010495218500070
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S2010495218500070?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Peter J. Brockwell & Jian Liu & Richard L. Tweedie, 1992. "On The Existence Of Stationary Threshold Autoregressive Moving‐Average Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(2), pages 95-107, March.
    2. Wai-Sum Chan & Albert Wong & Howell Tong, 2004. "Some Nonlinear Threshold Autoregressive Time Series Models for Actuarial Use," North American Actuarial Journal, Taylor & Francis Journals, vol. 8(4), pages 37-61.
    3. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    4. Li, Dong & Ling, Shiqing, 2012. "On the least squares estimation of multiple-regime threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 167(1), pages 240-253.
    5. Gao, Jiti & Tjøstheim, Dag & Yin, Jiying, 2013. "Estimation in threshold autoregressive models with a stationary and a unit root regime," Journal of Econometrics, Elsevier, vol. 172(1), pages 1-13.
    6. Sabiruzzaman, Md. & Monimul Huq, Md. & Beg, Rabiul Alam & Anwar, Sajid, 2010. "Modeling and forecasting trading volume index: GARCH versus TGARCH approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(2), pages 141-145, May.
    Full references (including those not matched with items on IDEAS)

    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. Yang, Yaxing & Ling, Shiqing, 2017. "Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 197(2), pages 368-381.
    2. Li, Dong & Tong, Howell, 2016. "Nested sub-sample search algorithm for estimation of threshold models," LSE Research Online Documents on Economics 68880, London School of Economics and Political Science, LSE Library.
    3. Victor V. Konev & Sergey E. Vorobeychikov, 2022. "Fixed accuracy estimation of parameters in a threshold autoregressive model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 685-711, August.
    4. repec:wyi:journl:002203 is not listed on IDEAS
    5. Francesco Giordano & Marcella Niglio & Cosimo Damiano Vitale, 2017. "Unit Root Testing in Presence of a Double Threshold Process," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 539-556, June.
    6. Jesús Gonzalo & Jean-Yves Pitarakis, 2013. "Estimation and inference in threshold type regime switching models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 8, pages 189-205, Edward Elgar Publishing.
    7. repec:hum:wpaper:sfb649dp2013-034 is not listed on IDEAS
    8. Thouraya Boujelbène Dammak & Kamel Helali, 2016. "A Nonlinear Approach to Tunisian Inflation Rate," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 147-164, September.
    9. Chen, Haiqiang, 2015. "Robust Estimation And Inference For Threshold Models With Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 31(4), pages 778-810, August.
    10. Greta Goracci, 2021. "An empirical study on the parsimony and descriptive power of TARMA models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 109-137, March.
    11. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    12. Shyh-Wei Chen, 2008. "Non-stationarity and Non-linearity in Stock Prices: Evidence from the OECD Countries," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-11.
    13. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    14. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(1), pages 113-127, April.
    15. Pitarakis Jean-Yves, 2006. "Model Selection Uncertainty and Detection of Threshold Effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-30, March.
    16. Janice Boucher Breuer & John McDermott, 2019. "Debt And Depression," Contemporary Economic Policy, Western Economic Association International, vol. 37(4), pages 714-730, October.
    17. Robert, Anderton & Baldwin, Richard & Taglioni, Daria, 2007. "The impact of monetary union on trade prices," Journal of Financial Transformation, Capco Institute, vol. 19, pages 35-48.
    18. Jian Li & Jean‐Paul Chavas, 2023. "A dynamic analysis of the distribution of commodity futures and spot prices," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(1), pages 122-143, January.
    19. Pawel Milobedzki, 2010. "The Term Structure of the Polish Interbank Rates. A Note on the Symmetry of their Reversion to the Mean," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 81-95.
    20. Liew, Venus Khim-Sen & Baharumshah, Ahmad Zubaidi & Habibullah, Muzafar Shah & Midi, Habshah, 2008. "Monetary exchange rate model: supportive evidence from nonlinear testing procedures," MPRA Paper 7293, University Library of Munich, Germany.
    21. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    22. Cheng-Hsun Lin & Nai-Fong Kuo & Cheng-Da Yuan, 2008. "Nonlinear vs. nonstationary of hysteresis in unemployment: evidence from OECD economies," Applied Economics Letters, Taylor & Francis Journals, vol. 15(11), pages 905-909.

    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:wsi:afexxx:v:13:y:2018:i:02:n:s2010495218500070. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/afe/afe.shtml .

    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.