IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v96y2021icp326-335.html
   My bibliography  Save this article

What determines volatility smile in China?

Author

Listed:
  • Li, Pengshi
  • Xian, Aichuan
  • Lin, Yan

Abstract

The implied volatility for 50 ETF options in China shows a significant smile pattern across different moneyness. Call and put options on 50 ETFs transacted from February 2015 to December 2018 are obtained. Regression and vector autoregression analyses are employed to investigate the structural relationship between the volatility smile and potential determinants. The determinants considered in this study include liquidity variables, market momentum, features of the underlying asset and time to maturity. The empirical results show that time to maturity and uncertainty of the underlying asset are the main determinants of the structure of the volatility smile. Moreover, realized volatility of the underlying asset and liquidity proxy variables, open interest and the trading volume of options contracts, have significant impact on the structure of the volatility smile.

Suggested Citation

  • Li, Pengshi & Xian, Aichuan & Lin, Yan, 2021. "What determines volatility smile in China?," Economic Modelling, Elsevier, vol. 96(C), pages 326-335.
    • Handle: RePEc:eee:ecmode:v:96:y:2021:i:c:p:326-335
    DOI: 10.1016/j.econmod.2020.04.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999319316931
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2020.04.013?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. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. "Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    2. Jimmy E. Hilliard & Haoran Zhang, 2019. "Regulatory Soft Interventions in the Chinese Market: Compliance Effects and Impact on Option Market Efficiency," The Financial Review, Eastern Finance Association, vol. 54(2), pages 265-301, May.
    3. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    4. repec:bla:jfinan:v:59:y:2004:i:2:p:711-753 is not listed on IDEAS
    5. Alessandro Beber, 2001. "Determinants of the implied volatility function on the Italian Stock Market," LEM Papers Series 2001/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Sheikh, Aamir M., 1991. "Transaction Data Tests of S&P 100 Call Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 26(4), pages 459-475, December.
    7. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    8. Rubinstein, Mark, 1994. "Implied Binomial Trees," Journal of Finance, American Finance Association, vol. 49(3), pages 771-818, July.
    9. Ignacio Peña & Gonzalo Rubio & Gregorio Serna, 2001. "Smiles, Bid‐ask Spreads and Option Pricing," European Financial Management, European Financial Management Association, vol. 7(3), pages 351-374, September.
    10. Mark Rubinstein., 1994. "Implied Binomial Trees," Research Program in Finance Working Papers RPF-232, University of California at Berkeley.
    11. Sanjay Sehgal & N. Vijayakumar, 2008. "Determinants of Implied Volatility Function on the Nifty Index Options Market: Evidence from India," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 4(1), pages 45-69.
    12. Gonzalo Rubio & Mikel Tapia, 1996. "Adverse selection, volume and transactions around dividend announcements in a continuous auction system," European Financial Management, European Financial Management Association, vol. 2(1), pages 39-67, March.
    13. Hassan Tanha & Michael Dempsey, 2015. "Do Aussie markets smile? Implied volatility functions and determinants," Applied Economics, Taylor & Francis Journals, vol. 47(30), pages 3143-3163, June.
    14. Pena, Ignacio & Rubio, Gonzalo & Serna, Gregorio, 1999. "Why do we smile? On the determinants of the implied volatility function," Journal of Banking & Finance, Elsevier, vol. 23(8), pages 1151-1179, August.
    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. Rachel R. Cheti & Bahati Ilembo, 2021. "Vector Autoregressive Approach After First Differencing: A Time Series Analysis Of Inflation And Its Determinants In Tanzania," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 6(2), pages 43-56, September.
    2. Linyu Wang & Yifan Ji & Zhongxin Ni, 2024. "Which implied volatilities contain more information? Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1896-1919, April.

    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. Narain & Narander Kumar Nigam & Piyush Pandey, 2016. "Behaviour and determinants of implied volatility in Indian market," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 13(3), pages 271-291, November.
    2. Jin Zhang & Yi Xiang, 2008. "The implied volatility smirk," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 263-284.
    3. Hsuan-Chu Lin & Ren-Raw Chen & Oded Palmon, 2016. "Explaining the volatility smile: non-parametric versus parametric option models," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 907-935, May.
    4. Soini, Vesa & Lorentzen, Sindre, 2019. "Option prices and implied volatility in the crude oil market," Energy Economics, Elsevier, vol. 83(C), pages 515-539.
    5. Pena, Ignacio & Rubio, Gonzalo & Serna, Gregorio, 1999. "Why do we smile? On the determinants of the implied volatility function," Journal of Banking & Finance, Elsevier, vol. 23(8), pages 1151-1179, August.
    6. Alessandro Beber, 2001. "Determinants of the implied volatility function on the Italian Stock Market," LEM Papers Series 2001/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. F. Leung & M. Law & S. K. Djeng, 2024. "Deterministic modelling of implied volatility in cryptocurrency options with underlying multiple resolution momentum indicator and non-linear machine learning regression algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    8. Chang, Eric C. & Ren, Jinjuan & Shi, Qi, 2009. "Effects of the volatility smile on exchange settlement practices: The Hong Kong case," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 98-112, January.
    9. Yue, Tian & Gehricke, Sebastian A. & Zhang, Jin E. & Pan, Zheyao, 2021. "The implied volatility smirk in the Chinese equity options market," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    10. Nikkinen, Jussi, 2003. "Normality tests of option-implied risk-neutral densities: evidence from the small Finnish market," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 99-116.
    11. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    12. Du Du & Dan Luo, 2019. "The Pricing of Jump Propagation: Evidence from Spot and Options Markets," Management Science, INFORMS, vol. 67(5), pages 2360-2387, May.
    13. Guidolin, Massimo & Timmermann, Allan, 2003. "Option prices under Bayesian learning: implied volatility dynamics and predictive densities," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 717-769, March.
    14. Gurdip Bakshi & Charles Cao & Zhaodong (Ken) Zhong, 2021. "Assessing models of individual equity option prices," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 1-28, July.
    15. Ferreira García, María Eva & Gago, Mónica & Rubio Irigoyen, Gonzalo, 1999. "A Semiparametric Estimation of Liquidity Effects on Option Pricing," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    16. Fiorentini, Gabriele & Leon, Angel & Rubio, Gonzalo, 2002. "Estimation and empirical performance of Heston's stochastic volatility model: the case of a thinly traded market," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 225-255, March.
    17. Stylianos Perrakis, 2022. "From innovation to obfuscation: continuous time finance fifty years later," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 369-401, September.
    18. Robert Tompkins, 2001. "Implied volatility surfaces: uncovering regularities for options on financial futures," The European Journal of Finance, Taylor & Francis Journals, vol. 7(3), pages 198-230.
    19. Ke Nian & Thomas F. Coleman & Yuying Li, 2018. "Learning minimum variance discrete hedging directly from the market," Quantitative Finance, Taylor & Francis Journals, vol. 18(7), pages 1115-1128, July.
    20. Don M. Chance & Thomas A. Hanson & Weiping Li & Jayaram Muthuswamy, 2017. "A bias in the volatility smile," Review of Derivatives Research, Springer, vol. 20(1), pages 47-90, April.

    More about this item

    Keywords

    Implied volatility; Volatility smile; Options; 50 ETF;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:ecmode:v:96:y:2021:i:c:p:326-335. 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/inca/30411 .

    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.