Forecasting Volatility and Pricing Option: An Empirical Evaluation of Indian Stock Market

Sunaina Kanojia, Neeraj Jain
2017 IOSR Journal of Business and Management  
The present study empirically investigates and examine seven models of volatility forecasting, namely unconditional standard deviation (also written as Long Term Moving Volatility), Standard GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, GJR-GARCH model, Exponential GARCH model (eGARCH), Asymmetric Power GARCH model (apGARCH), Component Standard GARCH model (csGARCH) , and Option Implied Volatility model to gauge the most appropriate model of volatility forecasting in
more » ... ifty constituent companies. The assessment of risk and determination of price of the asset class is primarily dependent on the volatility calculated for the class of asset. In view of obtaining precision in the process of determining the price of the option and making hedging most effective, it's imperative to have the most appropriate method of calculating the volatility. The present study finds option implied volatility as the best performing model except in few categories of option data where VIX outperformed. Similarly on empirical performance of Black-Scholes (BS) model the present study finds that performance is not same across various maturities which indicate volatility is not constant as assumed by BS model during the tenure of the study in Indian market. 8 | Page near the maturity. In this way, present study provide rationale for using more advanced model for pricing options and cautious to the investors who use BS model to price options.
doi:10.9790/487x-1907010108 fatcat:tnrbmrtyjfdajn566ia74ipyxq