In this article, the information content of implied volatility is studied at sub-periods (i.e., pre- and post-crises of 2007–09). The main objective is to judge the predictive power of implied volatility in the pre- and post-crises period, using at-the-money (ATM) non-overlapping monthly implied volatilities of Nifty Index options. A simple ordinary least squares (OLS) estimation is used to analyse the information content of implied volatility in sub-periods. An autoregressive-moving average (ARMA) structure is analysed for the assessment of times series property of ex-ante and ex-post volatility. An autoregressive distributed lag (ARDL) model is adopted to choose the most advantageous forecasting model for predicting the future volatility. The OLS estimation shows that implied volatility is more biased in the pre-crises period. The two-stage least squares (2SLS) estimation clearly explains that implied volatility is an unbiased estimate of the future realised volatility. An ARMA (1,1) and ARDL (1,0) is the best model of future volatility estimation. This study explains that for Indian derivative market, volatility estimates based on options are useful for the pricing of derivative instruments and portfolio risk management.
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