There is now an extensive literature on modeling the implied volatility surface (IVS) as a function of optionsβ strike prices and time to maturity. The polynomial parameterization is one of these approaches and it provides a simple and efficient way for practitioners to estimate implied volatility. This project tests the predictive capability of this methodology in the post-financial crisis market. Using data for the period from July 1st, 2012 to June 30th, 2015 for European puts and calls of the S&P 500 index options, we estimate a vector autoregressive model to capture the dynamics of the IVS. Our results show that this methodology has better predictive capability on IVS of index options in post-financial crisis market than on IVS of equity options in pre-financial crisis period
