This study examines the empirical performance of three model-based option valuation approaches in the KOSPI200 options market. We evaluate the in-sample pricing, out-of-sample pricing and hedging performance of the approaches based on the specification of option pricing models directly (a pricing model-based approach), on the pricing kernels implied by the option pricing models (an implied pricing kernel-based approach), and on parametric pricing kernels which are independently structured to have their own explicit functional forms (a parametric pricing kernel-based approach). Two option pricing models, a GARCH option pricing model and a Black-Scholes (BS) option pricing model, and their implied pricing kernels are analyzed and two parametric pricing kernel specifications suggested by Rosenberg and Engle (2002) are compared in a unified framework which extends the GARCH process of Duan (1995) to reflect the dynamics of asymmetric volatility. We find that the empirical performance of the approaches related to the GARCH and Black-Scholes option pricing models is moderately improved when we estimate the structural parameters using options data (options-based estimation) compared to the model performances when estimating the parameters using only a time-series of underlying returns data (underlying returns-based estimation). With the estimates under the underlying returns-based estimation, the pricing modelbased option valuation approach outperforms the implied pricing kernel-based option valuation approach for both the GARCH and BS option pricing models. However, with the estimates under the options-based estimation, this relationship is reversed in pricing OTM options in the case of the GARCH option pricing model. Although the BS option pricing model is generally the worst performer with the estimates under the underlying returns-based estimation, it yields better performance for pricing ITM options and similar performance for hedging compared to the GARCH option pricing model with the estimates under the options-based estimation. The option valuation approach based on the parametric pricing kernel of which functional form is a Chebyshev polynomial performs best out of all approaches and methods considered in this study