IDEAS home Printed from https://ideas.repec.org/a/spt/apfiba/v8y2018i1f8_1_1.html
   My bibliography  Save this article

The Research of the Periodic Features of Stock Index Volatility based on Hilbert-Huang Transformation

Author

Listed:
  • Xingfang Huang
  • Lianqian Yin

Abstract

The Hilbert-Huang Transform(HHT) algorithm which proposed in recent years escape itself from the requirement of linear and smooth, and it has a clear physical meaning. The data comes from the Shanghai Composite stock index which is decomposed by HHT. It consists of two parts, the first part is empirical mode decomposition(EMD)，the second part is the Hilbert Spectrum. Firstly it gives all Intrinsic Mode Function (IMF) which is decomposed from EMD an interpretation of its physical meaning and introduces the concept of average oscillation cycle and compared the speed of between typical rise and fall times of volatility. On one hand, reconstruct the IMF and estimate its distribution for the purpose of drawing the best characterization cycle of all reconstructed IMF. On the other hand, calculate the average oscillation cycle of the treated IMF and finally derive the quantitative relationship between the two kinds of cycles. At last, to find the curve fits well with the envelope line of each IMF which has been transformed by Hilbert function.  JEL classification numbers: C6 G17

Suggested Citation

  • Xingfang Huang & Lianqian Yin, 2018. "The Research of the Periodic Features of Stock Index Volatility based on Hilbert-Huang Transformation," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(1), pages 1-1.
    • Handle: RePEc:spt:apfiba:v:8:y:2018:i:1:f:8_1_1
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JAFB%2fVol%208_1_1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    2. S. James Press, 1967. "A Compound Events Model for Security Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 317-317.
    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. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    2. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
    3. Kaehler, Jürgen & Marnet, Volker, 1993. "Markov-switching models for exchange-rate dynamics and the pricing of foreign-currency options," ZEW Discussion Papers 93-03, ZEW - Leibniz Centre for European Economic Research.
    4. Calvet, Laurent E. & Fisher, Adlai J., 2008. "Multifrequency jump-diffusions: An equilibrium approach," Journal of Mathematical Economics, Elsevier, vol. 44(2), pages 207-226, January.
    5. Peter Fortune, 1999. "Are stock returns different over weekends? a jump diffusion analysis of the \"weekend effect\"," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 3-19.
    6. Mr. Noureddine Krichene, 2006. "Recent Dynamics of Crude Oil Prices," IMF Working Papers 2006/299, International Monetary Fund.
    7. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    8. Bottazzi, G. & Sapio, S. & Secchi, A., 2005. "Some statistical investigations on the nature and dynamics of electricity prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 54-61.
    9. David S. Bates, 1995. "Testing Option Pricing Models," NBER Working Papers 5129, National Bureau of Economic Research, Inc.
    10. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    11. Chenghu Ma, 2013. "MPS Risk Aversion and MV Analysis in Continuous Time with Lévy Jumps," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    12. Dilip B. Madan & Frank Milne, 1991. "Option Pricing With V. G. Martingale Components," Working Paper 1159, Economics Department, Queen's University.
    13. Dotsis, George & Psychoyios, Dimitris & Skiadopoulos, George, 2007. "An empirical comparison of continuous-time models of implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 31(12), pages 3584-3603, December.
    14. Paola Zerilli, 2005. "Option pricing and spikes in volatility: theoretical and empirical analysis," Money Macro and Finance (MMF) Research Group Conference 2005 76, Money Macro and Finance Research Group.
    15. Cui, Jing & Zhao, Hua, 2015. "Intraday jumps in China's Treasury bond market and macro news announcements," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 211-223.
    16. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, August.
    17. Jos'e E. Figueroa-L'opez & Ruoting Gong & Christian Houdr'e, 2012. "High-order short-time expansions for ATM option prices of exponential L\'evy models," Papers 1208.5520, arXiv.org, revised Apr 2014.
    18. Ait-Sahalia, Yacine, 2004. "Disentangling diffusion from jumps," Journal of Financial Economics, Elsevier, vol. 74(3), pages 487-528, December.
    19. Katherine B. Ensor & Yu Han & Barbara Ostdiek & Stuart M. Turnbull, 2020. "Dynamic jump intensities and news arrival in oil futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 292-325, July.
    20. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.

    More about this item

    Keywords

    Hilbert-Huang algorithm; EMD; IMF; average oscillation cycle; volatility.;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:spt:apfiba:v:8:y:2018:i:1:f:8_1_1. 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: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    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.