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Liquidity Considerations in Estimating Implied Volatility

Author

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  • Rohini Grover
  • Susan Thomas

Abstract

Some option series in the market are far less liquid than others. Market illiquidity can reduce the informativeness of option prices. In this paper, we propose alternative schemes to estimate implied volatility while reducing the importance attached to illiquid options. Using data for index options traded at the National Stock Exchange in India, we and that the performance of a liquidity weighted scheme is superior to that of more conventional schemes such as the vega weights, the volatility elasticity weights and the traditional vxo. Liquidity weights offers the possibility of improved implied volatility estimation in situations where there is strong cross-sectional variation in option market liquidity.
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Suggested Citation

  • Rohini Grover & Susan Thomas, 2012. "Liquidity Considerations in Estimating Implied Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(8), pages 714-741, August.
    • Handle: RePEc:wly:jfutmk:v:32:y:2012:i:8:p:714-741
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. New insights into the events on the Indian stock market in the mid-1990s
      by Ajay Shah in Ajay Shah's blog on 2012-04-11 22:22:00
    2. Interesting readings
      by Ajay Shah in Ajay Shah's blog on 2011-05-20 09:33:00
    3. The rupee: Frequently asked questions
      by Ajay Shah in Ajay Shah's blog on 2011-12-02 00:26:00
    4. Interesting Readings for May 20, 2011
      by Ajay Shah in Citizen Economists on 2011-05-20 22:20:24
    5. The rupee: Frequently asked questions
      by Ajay Shah in Citizen Economists on 2011-12-02 20:50:18
    6. New insights into the events on the Indian stock market in the mid-1990s
      by Ajay Shah in Citizen Economists on 2012-04-14 00:10:04

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    Cited by:

    1. Sankar, Ganesh & Ramachandran, Shankar & Lukose P J, Jijo, 2020. "Dynamics of variance risk premium: Evidence from India," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 321-334.
    2. Rohini Grover & Ajay Shah, 2014. "The imprecision of volatility indexes," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-031, Indira Gandhi Institute of Development Research, Mumbai, India.
    3. Chaiyuth Padungsaksawasdi & Robert T. Daigler, 2014. "The Return‐Implied Volatility Relation for Commodity ETFs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(3), pages 261-281, March.
    4. Alok Dixit & Shivam Singh, 2018. "Ad-Hoc Black–Scholes vis-à-vis TSRV-based Black–Scholes: Evidence from Indian Options Market," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 57-88, March.
    5. Sensoy, Ahmet & Omole, John, 2018. "Implied volatility indices: A review and extension in the Turkish case," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 151-161.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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