Efficiency of Indian Option Market: Estimation of Future Market Volatility Using Implied Volatility


  • Symbiosis Institute of Business Management Bengaluru (SIBM), Bengaluru, Karnataka, 560100, India


Forecasting volatility is a key process in pricing stock and index options. Accurate forecasting of future volatility would facilitate the traders and investors to make an informed decision. The study examines the market efficiency of exchange traded index options in India. We investigate the predictive power of implied volatility of Nifty index options in forecasting the future stock market volatility. The efficient market hypothesis believes that the implied contains all past information, thereby making it a superior volatility forecast for the underlying asset. Our study is based on the implied volatility of Nifty index options for the years between 2010 and 2018. In this paper, we compare the accuracy of expected future volatility using implied volatility concerning historical volatility. We study the implied volatility for Nifty 50 index option over the last seven years and compare the results against the ARMA model and historical forecasts to re-establish the superiority of implied volatility and efficiency of the Indian option market.


Historical Volatility, Implied Volatility, Volatility Forecast

Subject Discipline

Financial Management

Full Text:


Abhijeet Chandra and Thenmozhi M. (2015). On asymmetric relationship of India volatility index (India VIX) with stock market return and risk management, DECISION (Springer India). 42(1). https://www.researchgate.net/publication/273328438_On_Asymmetric_Relationship_of_India_Volatility_Index_India_VIX_with_Stock_ Market_Return_and_Risk_Management

Costas Siriopoulos and Athanasios Fassas (2009). Implied Volatility Indices – A Review, SSRN Electronic Journal. https://www.researchgate.net/publication/228231105_ Implied_Volatility_Indices_-_A_Review.

Christensen B.J. and Prabhala NR. (1998). The relation between implied and realized volatility, Journal of Financial Economics. 50(2):125–150. https://pdfs.semanticscholar.org/8180/6e9d63ecfa76fef96fe735e90d 20edc29fb8.pdf.

Emmanuel Anoruo and Vasudeva NR Murthy (2016). An examination of the REIT return–implied volatility relation: A frequency domain approach, Journal of Economics and Finance, Springer; Academy of Economics and Finance. 41(3): 581−94. https://ideas.repec.org/a/spr/jecfin/v43y2019i1d10.1007_s12197-018-9442-1.html.

Henry Huang, Kent Wang and Zhanglong Wang (2016). A test of efficiency for the S&P 500 index option market using the generalized spectrum method, Journal of Banking and Finance. 64(C):52−70. http://www.sciencedirect.com/science/article/pii/S0378426615003167.

Imlak Shaikh and Puja Padhi (2014a). Inter-temporal relationship between India VIX and Nifty equity index, DECISION (Springer India). 41(4). https://www.researchgate.net/publication/268882433_Inter-temporal_ relationship_between_India_VIX_and_Nifty_equity_ index

Imlak Shaikh and Puja Padhi (2016). On the relationship between implied volatility index and equity index returns, Journal of Economic Studies. 43(1):27−47. https://doi.org/10.1108/JES-12-2013-0198.

Karam Pal Narwal and Purva Chhabra (2018). An insight of implied volatility Vis-a-Vis its informational efficiency, association with underlying assets and spillovers effects, Asian Journal of Management. 9(2). http://ajmjournal.com/AbstractView.aspx?PID=2018-9-2-17.

Kumar, S. (2012). A first look at the properties of India’s volatility index, International Journal of Emerging Markets. 7(2). https://doi.org/10.1108/17468801211209938.

Percheklii, D. (2014). Comparison between implied and historical volatility forecasts: Evidence from the Russian stock market. A thesis submitted in partial fulfillment of the requirements for the degree of MA in Economic Analysis, Kyiv School of Economics; 34p. http://www.kse.org.ua/download.php?downloadid=393.


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