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Determinants of Implied Volatility Function on the Nifty Index Options Market: Evidence from India

Author

Listed:
  • Sanjay Sehgal

    (Department of Financial Studies, University of Delhi, South Campus, New Delhi -21, India)

  • N. Vijayakumar

    (ESC PAU, France)

Abstract
In this paper, we examine two important propositions for the Indian options market: (1) the relationship between implied volatility and moneyness referred to as volatility smile and (2) the potential determinants of the smile asymmetry. We use daily data for the S&P CNX Nifty index call and put options and the underlying market index for the calendar years 2004 and 2005. We find that the volatility functions exhibit a positive slope in the Indian context using alternative measures of moneyness, thus confirming the consistency of our findings. Our evidence on smile asymmetry is in contrast with findings for mature markets, which exhibit negative asymmetry profiles in general. This may be owing to differences in investors' behaviour and market microstructure between mature and emerging markets. We also show that historical volatility and time to expiration are the potential determinants of smile asymmetry in India, as is the case with international evidence. We feel that a strong theoretical foundation should be provided for this observable empirical phenomenon. Journal: Asian Academy of Management Journal of Accounting and Finance

Suggested Citation

  • 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.
    • Handle: RePEc:usm:journl:aamjaf00401_45-69
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    Citations

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    Cited by:

    1. Sonali Jain & Jayanth R. Varma & Sobhesh Kumar Agarwalla, 2019. "Indian equity options: Smile, risk premiums, and efficiency," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 150-163, February.
    2. 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.
    3. Kotzé, Antonie & Labuschagne, Coenraad C.A. & Nair, Merell L. & Padayachi, Nadine, 2013. "Arbitrage-free implied volatility surfaces for options on single stock futures," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 380-399.
    4. Itkin, Andrey, 2015. "To sigmoid-based functional description of the volatility smile," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 264-291.
    5. Li, Pengshi & Xian, Aichuan & Lin, Yan, 2021. "What determines volatility smile in China?," Economic Modelling, Elsevier, vol. 96(C), pages 326-335.
    6. Mihir Dash, 2019. "Modeling of implied volatility surfaces of nifty index options," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 1-11, September.
    7. Sanjay Sehgal & Vidisha Garg & Florent Deisting, 2012. "Relationship between cross sectional volatility and stock returns: Evidence From India," Post-Print hal-01881918, HAL.
    8. Sanjay Sehgal & Vidisha Garg, 2016. "Cross-sectional Volatility and Stock Returns: Evidence for Emerging Markets," Vikalpa: The Journal for Decision Makers, , vol. 41(3), pages 234-246, September.

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